subject:(Sensor Fusion)

1. Sampaio, Luiz Gustavo Moreira. Robust Orientation Estimation of a Mobile Camera for Interaction with Large Displays : 大画面ディスプレイに対するインタラクションのためのモバイルカメラの頑強な姿勢推定; ダイガメンディスプレイニタイスルインタラクションノタメノモバイルカメラノガンキョウナシセイスイテイ.

Degree: Nara Institute of Science and Technology / 奈良先端科学技術大学院大学

URL: http://hdl.handle.net/10061/10440

Subjects/Keywords: Sensor Fusion

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APA (6^th Edition):

Sampaio, L. G. M. (n.d.). Robust Orientation Estimation of a Mobile Camera for Interaction with Large Displays : 大画面ディスプレイに対するインタラクションのためのモバイルカメラの頑強な姿勢推定; ダイガメンディスプレイニタイスルインタラクションノタメノモバイルカメラノガンキョウナシセイスイテイ. (Thesis). Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Retrieved from http://hdl.handle.net/10061/10440

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Sampaio, Luiz Gustavo Moreira. “Robust Orientation Estimation of a Mobile Camera for Interaction with Large Displays : 大画面ディスプレイに対するインタラクションのためのモバイルカメラの頑強な姿勢推定; ダイガメンディスプレイニタイスルインタラクションノタメノモバイルカメラノガンキョウナシセイスイテイ.” Thesis, Nara Institute of Science and Technology / 奈良先端科学技術大学院大学. Accessed February 27, 2021. http://hdl.handle.net/10061/10440.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Sampaio, Luiz Gustavo Moreira. “Robust Orientation Estimation of a Mobile Camera for Interaction with Large Displays : 大画面ディスプレイに対するインタラクションのためのモバイルカメラの頑強な姿勢推定; ダイガメンディスプレイニタイスルインタラクションノタメノモバイルカメラノガンキョウナシセイスイテイ.” Web. 27 Feb 2021.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Sampaio LGM. Robust Orientation Estimation of a Mobile Camera for Interaction with Large Displays : 大画面ディスプレイに対するインタラクションのためのモバイルカメラの頑強な姿勢推定; ダイガメンディスプレイニタイスルインタラクションノタメノモバイルカメラノガンキョウナシセイスイテイ. [Internet] [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; [cited 2021 Feb 27]. Available from: http://hdl.handle.net/10061/10440.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Sampaio LGM. Robust Orientation Estimation of a Mobile Camera for Interaction with Large Displays : 大画面ディスプレイに対するインタラクションのためのモバイルカメラの頑強な姿勢推定; ダイガメンディスプレイニタイスルインタラクションノタメノモバイルカメラノガンキョウナシセイスイテイ. [Thesis]. Nara Institute of Science and Technology / 奈良先端科学技術大学院大学; Available from: http://hdl.handle.net/10061/10440

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

University of Sydney

2. Morton, Peter Michael. Multi-target tracking using appearance models for identity maintenance .

Degree: 2014, University of Sydney

URL: http://hdl.handle.net/2123/11644

► This thesis considers perception systems for urban environments. It focuses on the task of tracking dynamic objects and in particular on methods that can maintain… (more)

Subjects/Keywords: Robotics; Tracking; Sensor fusion

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APA (6^th Edition):

Morton, P. M. (2014). Multi-target tracking using appearance models for identity maintenance . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/11644

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Morton, Peter Michael. “Multi-target tracking using appearance models for identity maintenance .” 2014. Thesis, University of Sydney. Accessed February 27, 2021. http://hdl.handle.net/2123/11644.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Morton, Peter Michael. “Multi-target tracking using appearance models for identity maintenance .” 2014. Web. 27 Feb 2021.

Vancouver:

Morton PM. Multi-target tracking using appearance models for identity maintenance . [Internet] [Thesis]. University of Sydney; 2014. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/2123/11644.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Morton PM. Multi-target tracking using appearance models for identity maintenance . [Thesis]. University of Sydney; 2014. Available from: http://hdl.handle.net/2123/11644

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of New South Wales

3. Howarth, Blair David Sidney. Real time 3D mapping for small wall climbing robots.

Degree: Mechanical & Manufacturing Engineering, 2012, University of New South Wales

URL: http://handle.unsw.edu.au/1959.4/51598 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10265/SOURCE02?view=true

► Small wall climbing robots are useful because they can access difficult environmentswhich preclude the use of more traditional mobile robot configurations. This couldinclude an industrial… (more)

▼ Small wall climbing robots are useful because they can access difficult environmentswhich preclude the use of more traditional mobile robot configurations. This couldinclude an industrial plant or collapsed building which contains numerous obstaclesand enclosed spaces. These robots are very agile and they can move fully throughthree dimensional (3D) space by attaching to nearby surfaces. For autonomous operation,they need the ability to map their environment to allow navigation and motionplanning between footholds. This surface mapping must be performed onboard asline-of-sight and wireless communication may not always be available.As most of the methods used for robotic mapping and navigation were developedfor two dimensional usage, they do not scale well or generalise for 3D operation.Wall climbing robots require a 3D map of nearby surfaces to facilitate navigationbetween footholds. However, no suitable mapping method currently exists. A 3Dsurface mapping methodology is presented in this thesis to meet this need.The presented 3D mapping method is based on the fusion of range and visioninformation in a novel fashion. Sparse scans from a laser range finder and a lowresolution camera are used, along with feature extraction, to significantly reducethe computational cost. These features are then grouped together to act as a basisfor the surface fitting. Planar surfaces, with full uncertainty, are generated fromthe grouped range features with the image features being used to generate planarpolygon boundaries. These surfaces are then merged together to build a 3D mapsurrounding a particular foothold position.Both experimental and simulated datasets are used to validate the presentedsurface mapping method. The surface fitting error is satisfactory and within therequired tolerances of a wall climbing robot prototype. An analysis of the computationalcost, along with experimental runtime results, indicates that onboard realtime operation is also achievable. The presented surface mapping methodology willtherefore allow small wall climbing robots to generate real time 3D environmentalmaps. This is an important step towards achieving autonomous operation. Advisors/Committee Members: Katupitiya, Jayantha, Mechanical & Manufacturing Engineering, Faculty of Engineering, UNSW, Guivant, Jose, Mechanical & Manufacturing Engineering, Faculty of Engineering, UNSW.

Subjects/Keywords: Sensor Fusion; 3D Mapping; Robotics

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APA (6^th Edition):

Howarth, B. D. S. (2012). Real time 3D mapping for small wall climbing robots. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/51598 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10265/SOURCE02?view=true

Chicago Manual of Style (16^th Edition):

Howarth, Blair David Sidney. “Real time 3D mapping for small wall climbing robots.” 2012. Doctoral Dissertation, University of New South Wales. Accessed February 27, 2021. http://handle.unsw.edu.au/1959.4/51598 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10265/SOURCE02?view=true.

MLA Handbook (7^th Edition):

Howarth, Blair David Sidney. “Real time 3D mapping for small wall climbing robots.” 2012. Web. 27 Feb 2021.

Vancouver:

Howarth BDS. Real time 3D mapping for small wall climbing robots. [Internet] [Doctoral dissertation]. University of New South Wales; 2012. [cited 2021 Feb 27]. Available from: http://handle.unsw.edu.au/1959.4/51598 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10265/SOURCE02?view=true.

Council of Science Editors:

Howarth BDS. Real time 3D mapping for small wall climbing robots. [Doctoral Dissertation]. University of New South Wales; 2012. Available from: http://handle.unsw.edu.au/1959.4/51598 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10265/SOURCE02?view=true

University of New South Wales

4. Laird, John. Modelling the impact of sensor placement and fusion for traffic monitoring.

Degree: Computer Science & Engineering, 2013, University of New South Wales

URL: http://handle.unsw.edu.au/1959.4/53000 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:11678/SOURCE01?view=true

► This thesis develops models to evaluate the impact of multi-modal sensor placement configurations on obtaining traffic parameters required for a variety of traffic monitoring and… (more)

▼ This thesis develops models to evaluate the impact of multi-modal sensor placement configurations on obtaining traffic parameters required for a variety of traffic monitoring and management applications.Existing traffic management strategies generally rely on the commonly used induction loop sensors, which are highly accurate presence detectors, however they have a limited sensing area. Alternate sensor modalities may provide a higher information gain in comparison, especially vision based sensors. An inherent problem with using vision based sensors in traffic management is the occlusion between vehicles, which can make detection of individual vehicles difficult.Information fusion from multiple sensors provides much richer information for scene understanding, leading to a greater ability to coordinate traffic management efficiently. Thus, effective sensor placement and fusion of data can improve the efficiency of traffic management. The aim of this thesis is to evaluate the impact of multi-modal sensor placement, and as a result improve the estimation accuracy of road traffic parameters obtained from various sensor configurations. More specifically, vision based sensors are studied, and later fused with inductive loops.In order to achieve this, models are developed to simulate various traffic flows, and to ensure consistency and relevance of the simulations to real world traffic. Models for single sensor modality and multi-modal sensor fusion are developed and are also validated. These models enable evaluation of sensor placement configurations to determine effectiveness for specific traffic applications.Results of various single sensor configurations demonstrate that the impact of view occlusion on the ability to detect vehicles can be improved by considering sensor placement. Combining inductive loops and video cameras by sensor fusion was found to overcome the problem of occlusion, resulting in a decided improvement in parameter estimation for traffic management and monitoring applications. For example, the sensor fusion models developed resulted in the queue length estimation accuracy being improved by up to 20%. Finally, by applying the models presented in this thesis to current ramp metering strategies, viable alternative sensor deployment solutions are recommended. Advisors/Committee Members: Chou, Chun Tung, Computer Science & Engineering, Faculty of Engineering, UNSW, Geers, D. Glenn, NICTA, Wang, Yang, NICTA.

Subjects/Keywords: Traffic management; Sensor placement; Sensor fusion

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APA (6^th Edition):

Laird, J. (2013). Modelling the impact of sensor placement and fusion for traffic monitoring. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/53000 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:11678/SOURCE01?view=true

Chicago Manual of Style (16^th Edition):

Laird, John. “Modelling the impact of sensor placement and fusion for traffic monitoring.” 2013. Doctoral Dissertation, University of New South Wales. Accessed February 27, 2021. http://handle.unsw.edu.au/1959.4/53000 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:11678/SOURCE01?view=true.

MLA Handbook (7^th Edition):

Laird, John. “Modelling the impact of sensor placement and fusion for traffic monitoring.” 2013. Web. 27 Feb 2021.

Vancouver:

Laird J. Modelling the impact of sensor placement and fusion for traffic monitoring. [Internet] [Doctoral dissertation]. University of New South Wales; 2013. [cited 2021 Feb 27]. Available from: http://handle.unsw.edu.au/1959.4/53000 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:11678/SOURCE01?view=true.

Council of Science Editors:

Laird J. Modelling the impact of sensor placement and fusion for traffic monitoring. [Doctoral Dissertation]. University of New South Wales; 2013. Available from: http://handle.unsw.edu.au/1959.4/53000 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:11678/SOURCE01?view=true

Penn State University

5. Sinsley, Gregory. Distributed Data Fusion Across Multiple Hard and Soft Mobile Sensor Platforms.

Degree: 2012, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/16157

► One of the biggest challenges currently facing the robotics field is sensor data fusion. Unmanned robots carry many sophisticated sensors including visual and infrared cameras,… (more)

Subjects/Keywords: sensor data fusion; information fusion; soft sensor data fusion; random set theory; particle filter

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APA (6^th Edition):

Sinsley, G. (2012). Distributed Data Fusion Across Multiple Hard and Soft Mobile Sensor Platforms. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/16157

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Sinsley, Gregory. “Distributed Data Fusion Across Multiple Hard and Soft Mobile Sensor Platforms.” 2012. Thesis, Penn State University. Accessed February 27, 2021. https://submit-etda.libraries.psu.edu/catalog/16157.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Sinsley, Gregory. “Distributed Data Fusion Across Multiple Hard and Soft Mobile Sensor Platforms.” 2012. Web. 27 Feb 2021.

Vancouver:

Sinsley G. Distributed Data Fusion Across Multiple Hard and Soft Mobile Sensor Platforms. [Internet] [Thesis]. Penn State University; 2012. [cited 2021 Feb 27]. Available from: https://submit-etda.libraries.psu.edu/catalog/16157.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sinsley G. Distributed Data Fusion Across Multiple Hard and Soft Mobile Sensor Platforms. [Thesis]. Penn State University; 2012. Available from: https://submit-etda.libraries.psu.edu/catalog/16157

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of California – Santa Cruz

6. Bruce, Jonathan. Design, Building, Testing, and Control of SUPERball: A Tensegrity Robot to Enable New Forms of Planetary Exploration.

Degree: Computer Engineering (Robotics and Control), 2016, University of California – Santa Cruz

URL: http://www.escholarship.org/uc/item/0274v214

► Presented in this work are the concepts to build, sense and control a completely untethered tensegrity robotic system called SUPERball (Spherical Underactuated Planetary Exploration Robot),… (more)

Subjects/Keywords: Robotics; Machine Learning; Robotics; Sensor Fusion; Tensegrity

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APA (6^th Edition):

Bruce, J. (2016). Design, Building, Testing, and Control of SUPERball: A Tensegrity Robot to Enable New Forms of Planetary Exploration. (Thesis). University of California – Santa Cruz. Retrieved from http://www.escholarship.org/uc/item/0274v214

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Bruce, Jonathan. “Design, Building, Testing, and Control of SUPERball: A Tensegrity Robot to Enable New Forms of Planetary Exploration.” 2016. Thesis, University of California – Santa Cruz. Accessed February 27, 2021. http://www.escholarship.org/uc/item/0274v214.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Bruce, Jonathan. “Design, Building, Testing, and Control of SUPERball: A Tensegrity Robot to Enable New Forms of Planetary Exploration.” 2016. Web. 27 Feb 2021.

Vancouver:

Bruce J. Design, Building, Testing, and Control of SUPERball: A Tensegrity Robot to Enable New Forms of Planetary Exploration. [Internet] [Thesis]. University of California – Santa Cruz; 2016. [cited 2021 Feb 27]. Available from: http://www.escholarship.org/uc/item/0274v214.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bruce J. Design, Building, Testing, and Control of SUPERball: A Tensegrity Robot to Enable New Forms of Planetary Exploration. [Thesis]. University of California – Santa Cruz; 2016. Available from: http://www.escholarship.org/uc/item/0274v214

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Penn State University

7. Wen, Yicheng. Heterogeneous Sensor Fusion in Sensor Networks: A Language-theoretic Approach .

Degree: 2011, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/12213

► This dissertation presents a framework for feature-level heterogeneous sensor data fusion in sensor networks via a language-theoretic approach. Probabilistic finite state automata (PFSA) are used… (more)

▼ This dissertation presents a framework for feature-level heterogeneous sensor data fusion in sensor networks via a language-theoretic approach. Probabilistic finite state automata (PFSA) are used to model the semantic patterns in the observations of the sensors. A novel pattern discovery algorithm is developed to extract the PFSA model from symbol sequences. It is shown that this algorithm can capture semantic structures more effectively than the existing techniques. In order to formulate the data fusion problem for semantic features, a link is established between the formal language theory and functional analysis by constructing a Hilbert space over a class of stochastic regular languages represented by PFSA. New algebraic operations are defined for PFSA with a family of parametrized inner products. The norm induced by the inner product is interpreted as a measure of the information contained in PFSA. Applications of this technique are discussed in the following areas: a) Orthogonal projection in the Hilbert space to solve the model reduction problem of PFSA. Numerical examples and experimental results are provided to elucidate the process of model order reduction. b) Supervised learning of semantic features of heterogeneous sensor data in the product Hilbert space. The semantic features are combined optimally for classification using linear discriminant analysis (LDA). The proposed algorithm has a set of parameters that can be potentially configured by the users to adapt the algorithm to environment changes. The proposed algorithm is validated for object recognition at the US-Mexican border. An architecture of fusion-driven sensor networks is introduced to incorporate the proposed fusion framework in sensor networks. The network protocol, called dynamic time-space clustering (DSTC), and its heterogeneous version, are designed to adapt the network to the fusion algorithms. A sensor network for selectively tracking mobile targets is implemented in the network simulator NS-2 for both homogeneous and heterogeneous sensor fields in an urban scenario for validating the propose architecture. Advisors/Committee Members: Asok Ray, Dissertation Advisor/Co-Advisor, Asok Ray, Committee Chair/Co-Chair, Shashi Phoha, Committee Chair/Co-Chair, Qiang Du, Committee Member, Alok Sinha, Committee Member, Qian Wang, Committee Member, Ishanu Chattopadhyay, Committee Member.

Subjects/Keywords: wireless sensor network; pattern recognition; Information fusion

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APA (6^th Edition):

Wen, Y. (2011). Heterogeneous Sensor Fusion in Sensor Networks: A Language-theoretic Approach . (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/12213

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Wen, Yicheng. “Heterogeneous Sensor Fusion in Sensor Networks: A Language-theoretic Approach .” 2011. Thesis, Penn State University. Accessed February 27, 2021. https://submit-etda.libraries.psu.edu/catalog/12213.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Wen, Yicheng. “Heterogeneous Sensor Fusion in Sensor Networks: A Language-theoretic Approach .” 2011. Web. 27 Feb 2021.

Vancouver:

Wen Y. Heterogeneous Sensor Fusion in Sensor Networks: A Language-theoretic Approach . [Internet] [Thesis]. Penn State University; 2011. [cited 2021 Feb 27]. Available from: https://submit-etda.libraries.psu.edu/catalog/12213.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wen Y. Heterogeneous Sensor Fusion in Sensor Networks: A Language-theoretic Approach . [Thesis]. Penn State University; 2011. Available from: https://submit-etda.libraries.psu.edu/catalog/12213

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

8. Aeberhard, Michael Peter. Object-level fusion for surround environment perception in automated driving applications.

Degree: 2017, Technische Universität Dortmund

URL: http://dx.doi.org/10.17877/DE290R-18029

► Driver assistance systems have increasingly relied on more sensors for new functions. As advanced driver assistance system continue to improve towards automated driving, new methods… (more)

Subjects/Keywords: Autonomes Fahren; Perzeption; Sensor Daten Fusion; 620

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APA (6^th Edition):

Aeberhard, M. P. (2017). Object-level fusion for surround environment perception in automated driving applications. (Doctoral Dissertation). Technische Universität Dortmund. Retrieved from http://dx.doi.org/10.17877/DE290R-18029

Chicago Manual of Style (16^th Edition):

Aeberhard, Michael Peter. “Object-level fusion for surround environment perception in automated driving applications.” 2017. Doctoral Dissertation, Technische Universität Dortmund. Accessed February 27, 2021. http://dx.doi.org/10.17877/DE290R-18029.

MLA Handbook (7^th Edition):

Aeberhard, Michael Peter. “Object-level fusion for surround environment perception in automated driving applications.” 2017. Web. 27 Feb 2021.

Vancouver:

Aeberhard MP. Object-level fusion for surround environment perception in automated driving applications. [Internet] [Doctoral dissertation]. Technische Universität Dortmund; 2017. [cited 2021 Feb 27]. Available from: http://dx.doi.org/10.17877/DE290R-18029.

Council of Science Editors:

Aeberhard MP. Object-level fusion for surround environment perception in automated driving applications. [Doctoral Dissertation]. Technische Universität Dortmund; 2017. Available from: http://dx.doi.org/10.17877/DE290R-18029

Linköping University

9. Alsén, Victoria. GNSS Aided Inertial Human Body Motion Capture.

Degree: Automatic Control, 2016, Linköping University

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-133291

► Human body motion capture systems based on inertial sensors (gyroscopes andaccelerometers) are able to track the relative motions in the body precisely, oftenwith the… (more)

▼ Human body motion capture systems based on inertial sensors (gyroscopes andaccelerometers) are able to track the relative motions in the body precisely, oftenwith the aid of supplementary sensors. The sensor measurements are combinedthrough a sensor fusion algorithm to create estimates of, among other parame-ters, position, velocity and orientation for each body segment. As this algorithmrequires integration of noisy measurements, some drift, especially in the positionestimate, is expected. Taking advantage of the knowledge about the tracked sub-ject, a human body, models have been developed that improve the estimates, butposition still displays drift over time.In this thesis, a GNSS receiver is added to the motion capture system to givea drift-free measurement of the position as well as a velocity measurement. Theinertial data and the GNSS data complements each other well, particularly interms of observability of global and relative motions. To enable the models of thehuman body at an early stage of the fusion of sensor data, an optimization basedmaximum a posteriori algorithm was used, which is also better suited for thenonlinear system tracked compared to the conventional method of using Kalmanfilters.One of the models that improves the position estimate greatly, without addingadditional sensing, is the contact detection, with which the velocity of a segmentis set to zero whenever it is considered stationary in comparison to the surround-ing environment, e.g. when a foot touches the ground. This thesis looks at botha scenario when this contact detection can be applied and a scenario where itcannot be applied, to see what possibilities an addition of GNSS sensor couldbring to the human body motion tracking case. The results display a notable im-provement in position, both with and without contact detection. Furthermore,the heading estimate is improved at a full-body scale and the solution makes theestimates depend less on acceleration bias estimation.These results show great potential for more accurate estimates outdoors andcould prove valuable for enabling motion tracking of scenarios where the contactdetection model cannot be used, such as e.g. biking.

Subjects/Keywords: sensor fusion; GNSS; IMU; Control Engineering; Reglerteknik

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APA (6^th Edition):

Alsén, V. (2016). GNSS Aided Inertial Human Body Motion Capture. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-133291

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Alsén, Victoria. “GNSS Aided Inertial Human Body Motion Capture.” 2016. Thesis, Linköping University. Accessed February 27, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-133291.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Alsén, Victoria. “GNSS Aided Inertial Human Body Motion Capture.” 2016. Web. 27 Feb 2021.

Vancouver:

Alsén V. GNSS Aided Inertial Human Body Motion Capture. [Internet] [Thesis]. Linköping University; 2016. [cited 2021 Feb 27]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-133291.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Alsén V. GNSS Aided Inertial Human Body Motion Capture. [Thesis]. Linköping University; 2016. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-133291

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

10. Nilsson, Sanna. Sensor Fusion for Heavy Duty Vehicle Platooning.

Degree: The Institute of Technology, 2012, Linköping UniversityLinköping University

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-78970

► The aim of platooning is to enable several Heavy Duty Vehicles (HDVs) to drive in a convoy and act as one unit to decrease the… (more)

Subjects/Keywords: Extended Kalman Filter; EKF; platooning; sensor fusion

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APA (6^th Edition):

Nilsson, S. (2012). Sensor Fusion for Heavy Duty Vehicle Platooning. (Thesis). Linköping UniversityLinköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-78970

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Nilsson, Sanna. “Sensor Fusion for Heavy Duty Vehicle Platooning.” 2012. Thesis, Linköping UniversityLinköping University. Accessed February 27, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-78970.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Nilsson, Sanna. “Sensor Fusion for Heavy Duty Vehicle Platooning.” 2012. Web. 27 Feb 2021.

Vancouver:

Nilsson S. Sensor Fusion for Heavy Duty Vehicle Platooning. [Internet] [Thesis]. Linköping UniversityLinköping University; 2012. [cited 2021 Feb 27]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-78970.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nilsson S. Sensor Fusion for Heavy Duty Vehicle Platooning. [Thesis]. Linköping UniversityLinköping University; 2012. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-78970

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

11. Carisi, Stefano (author). Multimodal Sensor-Fusion for Context-Aware Semi-Autonomous Control of a Multi Degree-of-Freedom Upper Limb Prosthesis.

Degree: 2018, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:df9c8c3f-ba3b-4616-870a-5cbbda76ff1b

► Objective. Dexterous control of myoelectric upper limb prosthesis is still limited by the capabilities of the modern human-machine interfaces. The first goal of the current… (more)

▼ Objective. Dexterous control of myoelectric upper limb prosthesis is still limited by the capabilities of the modern human-machine interfaces. The first goal of the current work was to develop a system that supplements the academic myoelectric state-of-the-art interface during the interaction with objects (e.g., grasping, manipulation) with the goal of increasing the overall performances and robustness of the prosthetic device. Additionally, the current study aims to define guidelines for a larger-scale experiment to be performed in the immediate future. Approach. I developed algorithms, which provide context- and user-awareness to the system by fusing multimodal sensory input data, and a control scheme that employs such context-awareness to estimate the user’s grasp intentions to automatically preshape the prosthesis for grasping in real time. The control scheme was compared against the major academic state-of-the-art myoelectric control scheme (i.e., pattern recognition) in two able-bodied subjects. The experimental tests consisted of grasping, reorienting, and relocating sets of common objects using a multi-degree-of-freedom prosthesis with two grip types and two degrees-of-freedom actuated wrist. Main Results. The proposed semi-autonomous system was able to function in realistic and time-varying cluttered environments. The obtained results illustrate better and more consistent performances (i.e., lower task completion time and standard deviation) of the developed control scheme with respect to the state-of-the-art counterpart. Improvements in control robustness during object manipulation (i.e., lower number of object drops) have also been obtained. The current study helped in defining guidelines for the future larger-scale experiment: more than one experimental session, data logging and subjective measurements recording. Significance. The proposed system improves multiple aspects involved in the control of myoelectric multi-degree-of-freedom upper limb prostheses. The guidelines defined in this work, are essential for evaluating, during the future larger-scale study, the impact of the proposed system on users’ experience (e.g., workload and ease of use). Advisors/Committee Members: Plettenburg, Dick (mentor), Markovic, Marko (graduation committee), Abbink, David (graduation committee), van der Helm, Frans (graduation committee), Smit, Gerwin (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: sensor-fusion context-aware upper limb prosthesis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Carisi, S. (. (2018). Multimodal Sensor-Fusion for Context-Aware Semi-Autonomous Control of a Multi Degree-of-Freedom Upper Limb Prosthesis. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:df9c8c3f-ba3b-4616-870a-5cbbda76ff1b

Chicago Manual of Style (16^th Edition):

Carisi, Stefano (author). “Multimodal Sensor-Fusion for Context-Aware Semi-Autonomous Control of a Multi Degree-of-Freedom Upper Limb Prosthesis.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:df9c8c3f-ba3b-4616-870a-5cbbda76ff1b.

MLA Handbook (7^th Edition):

Carisi, Stefano (author). “Multimodal Sensor-Fusion for Context-Aware Semi-Autonomous Control of a Multi Degree-of-Freedom Upper Limb Prosthesis.” 2018. Web. 27 Feb 2021.

Vancouver:

Carisi S(. Multimodal Sensor-Fusion for Context-Aware Semi-Autonomous Control of a Multi Degree-of-Freedom Upper Limb Prosthesis. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:df9c8c3f-ba3b-4616-870a-5cbbda76ff1b.

Council of Science Editors:

Carisi S(. Multimodal Sensor-Fusion for Context-Aware Semi-Autonomous Control of a Multi Degree-of-Freedom Upper Limb Prosthesis. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:df9c8c3f-ba3b-4616-870a-5cbbda76ff1b

Delft University of Technology

12. GAO, Xinyu (author). Sensor Data Fusion of Lidar and Camera for Road User Detection.

Degree: 2018, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:e310da67-98b2-4288-b656-15da36e3f12a

►

Object detection is one of the most important research topics in autonomous vehicles. The detection systems of autonomous vehicles nowadays are mostly image-based ones which… (more)

Subjects/Keywords: 3D object detection; Lidar; Camera; sensor fusion

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APA (6^th Edition):

GAO, X. (. (2018). Sensor Data Fusion of Lidar and Camera for Road User Detection. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:e310da67-98b2-4288-b656-15da36e3f12a

Chicago Manual of Style (16^th Edition):

GAO, Xinyu (author). “Sensor Data Fusion of Lidar and Camera for Road User Detection.” 2018. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:e310da67-98b2-4288-b656-15da36e3f12a.

MLA Handbook (7^th Edition):

GAO, Xinyu (author). “Sensor Data Fusion of Lidar and Camera for Road User Detection.” 2018. Web. 27 Feb 2021.

Vancouver:

GAO X(. Sensor Data Fusion of Lidar and Camera for Road User Detection. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:e310da67-98b2-4288-b656-15da36e3f12a.

Council of Science Editors:

GAO X(. Sensor Data Fusion of Lidar and Camera for Road User Detection. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:e310da67-98b2-4288-b656-15da36e3f12a

13. Sentkerestiová Jana. Development of Hall sensors for steady state magnetic diagnostic of fusion reactors .

Degree: 2014, Czech University of Technology

URL: http://hdl.handle.net/10467/20229

Hall sensors development and evaluation for fusion reactors; Hall sensors development and evaluation for fusion reactors Advisors/Committee Members: Ďuran Ivan (advisor).

Subjects/Keywords: Hall sensor; magnetic diagnostics; fusion reators; ITER

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APA (6^th Edition):

Jana, S. (2014). Development of Hall sensors for steady state magnetic diagnostic of fusion reactors . (Thesis). Czech University of Technology. Retrieved from http://hdl.handle.net/10467/20229

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Jana, Sentkerestiová. “Development of Hall sensors for steady state magnetic diagnostic of fusion reactors .” 2014. Thesis, Czech University of Technology. Accessed February 27, 2021. http://hdl.handle.net/10467/20229.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Jana, Sentkerestiová. “Development of Hall sensors for steady state magnetic diagnostic of fusion reactors .” 2014. Web. 27 Feb 2021.

Vancouver:

Jana S. Development of Hall sensors for steady state magnetic diagnostic of fusion reactors . [Internet] [Thesis]. Czech University of Technology; 2014. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/10467/20229.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Jana S. Development of Hall sensors for steady state magnetic diagnostic of fusion reactors . [Thesis]. Czech University of Technology; 2014. Available from: http://hdl.handle.net/10467/20229

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Georgia Tech

14. Liu, Kaibo. Data fusion for system modeling, performance assessment and improvement.

Degree: PhD, Industrial and Systems Engineering, 2013, Georgia Tech

URL: http://hdl.handle.net/1853/52937

► Due to rapid advancements in sensing and computation technology, multiple types of sensors have been embedded in various applications, on-line automatically collecting massive production information.… (more)

▼ Due to rapid advancements in sensing and computation technology, multiple types of sensors have been embedded in various applications, on-line automatically collecting massive production information. Although this data-rich environment provides great opportunity for more effective process control, it also raises new research challenges on data analysis and decision making due to the complex data structures, such as heterogeneous data dependency, and large-volume and high-dimensional characteristics. This thesis contributes to the area of System Informatics and Control (SIAC) to develop systematic data fusion methodologies for effective quality control and performance improvement in complex systems. These advanced methodologies enable (1) a better handling of the rich data environment communicated by complex engineering systems, (2) a closer monitoring of the system status, and (3) a more accurate forecasting of future trends and behaviors. The research bridges the gaps in methodologies among advanced statistics, engineering domain knowledge and operation research. It also forms close linkage to various application areas such as manufacturing, health care, energy and service systems. This thesis started from investigating the optimal sensor system design and conducting multiple sensor data fusion analysis for process monitoring and diagnosis in different applications. In Chapter 2, we first studied the couplings or interactions between the optimal design of a sensor system in a Bayesian Network and quality management of a manufacturing system, which can improve cost-effectiveness and production yield by considering sensor cost, process change detection speed, and fault diagnosis accuracy in an integrated manner. An algorithm named “Best Allocation Subsets by Intelligent Search” (BASIS) with optimality proof is developed to obtain the optimal sensor allocation design at minimum cost under different user specified detection requirements. Chapter 3 extended this line of research by proposing a novel adaptive sensor allocation framework, which can greatly improve the monitoring and diagnosis capabilities of the previous method. A max-min criterion is developed to manage sensor reallocation and process change detection in an integrated manner. The methodology was tested and validated based on a hot forming process and a cap alignment process. Next in Chapter 4, we proposed a Scalable-Robust-Efficient Adaptive (SERA) sensor allocation strategy for online high-dimensional process monitoring in a general network. A monitoring scheme of using the sum of top-r local detection statistics is developed, which is scalable, effective and robust in detecting a wide range of possible shifts in all directions. This research provides a generic guideline for practitioners on determining (1) the appropriate sensor layout; (2) the “ON” and “OFF” states of different sensors; and (3) which part of the acquired data should be transmitted to and analyzed at the fusion center, when only limited resources are available. To improve the… Advisors/Committee Members: Shi, Jianjun (advisor), Gebraeel, Nagi (committee member), Mei, Yajun (committee member), Kvam, Paul (committee member), Li, Jing (committee member).

Subjects/Keywords: Data fusion; Multiple Sensors; Sensor allocation; Prognostics

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APA (6^th Edition):

Liu, K. (2013). Data fusion for system modeling, performance assessment and improvement. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52937

Chicago Manual of Style (16^th Edition):

Liu, Kaibo. “Data fusion for system modeling, performance assessment and improvement.” 2013. Doctoral Dissertation, Georgia Tech. Accessed February 27, 2021. http://hdl.handle.net/1853/52937.

MLA Handbook (7^th Edition):

Liu, Kaibo. “Data fusion for system modeling, performance assessment and improvement.” 2013. Web. 27 Feb 2021.

Vancouver:

Liu K. Data fusion for system modeling, performance assessment and improvement. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/1853/52937.

Council of Science Editors:

Liu K. Data fusion for system modeling, performance assessment and improvement. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/52937

University of Georgia

15. Bottone, Michael Anthony. A system to bring real time reconstructions of objects into the virtual environment for use in interaction-intensive applications.

Degree: 2016, University of Georgia

URL: http://hdl.handle.net/10724/35569"

► Bringing real objects into the virtual world has been shown to increase usability and presence in virtual reality applications. This paper presents a system to… (more)

Subjects/Keywords: Virtual Reality; Sensor Fusion; Human Computer Interaction

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APA (6^th Edition):

Bottone, M. A. (2016). A system to bring real time reconstructions of objects into the virtual environment for use in interaction-intensive applications. (Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/35569"

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Bottone, Michael Anthony. “A system to bring real time reconstructions of objects into the virtual environment for use in interaction-intensive applications.” 2016. Thesis, University of Georgia. Accessed February 27, 2021. http://hdl.handle.net/10724/35569".

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Bottone, Michael Anthony. “A system to bring real time reconstructions of objects into the virtual environment for use in interaction-intensive applications.” 2016. Web. 27 Feb 2021.

Vancouver:

Bottone MA. A system to bring real time reconstructions of objects into the virtual environment for use in interaction-intensive applications. [Internet] [Thesis]. University of Georgia; 2016. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/10724/35569".

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bottone MA. A system to bring real time reconstructions of objects into the virtual environment for use in interaction-intensive applications. [Thesis]. University of Georgia; 2016. Available from: http://hdl.handle.net/10724/35569"

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

16. Moyers Barrera, Gerardo (author). Sensor Fusion for Localization of Autonomous Ground Drone in Indoor Environments.

Degree: 2020, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:af31d773-3d35-49fe-b48f-b950c17a7a64

►

Technology is transforming almost all aspects of our lives, one of them is automation. The main motivation of automation is to help humans avoid performing… (more)

Subjects/Keywords: Localization; Sensor Fusion; Real-time; Low-cost

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APA (6^th Edition):

Moyers Barrera, G. (. (2020). Sensor Fusion for Localization of Autonomous Ground Drone in Indoor Environments. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:af31d773-3d35-49fe-b48f-b950c17a7a64

Chicago Manual of Style (16^th Edition):

Moyers Barrera, Gerardo (author). “Sensor Fusion for Localization of Autonomous Ground Drone in Indoor Environments.” 2020. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:af31d773-3d35-49fe-b48f-b950c17a7a64.

MLA Handbook (7^th Edition):

Moyers Barrera, Gerardo (author). “Sensor Fusion for Localization of Autonomous Ground Drone in Indoor Environments.” 2020. Web. 27 Feb 2021.

Vancouver:

Moyers Barrera G(. Sensor Fusion for Localization of Autonomous Ground Drone in Indoor Environments. [Internet] [Masters thesis]. Delft University of Technology; 2020. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:af31d773-3d35-49fe-b48f-b950c17a7a64.

Council of Science Editors:

Moyers Barrera G(. Sensor Fusion for Localization of Autonomous Ground Drone in Indoor Environments. [Masters Thesis]. Delft University of Technology; 2020. Available from: http://resolver.tudelft.nl/uuid:af31d773-3d35-49fe-b48f-b950c17a7a64

University of South Carolina

17. Rahman, Sharmin. A Multi-Sensor Fusion-Based Underwater Slam System.

Degree: PhD, Computer Science and Engineering, 2020, University of South Carolina

URL: https://scholarcommons.sc.edu/etd/5987

► This dissertation addresses the problem of real-time Simultaneous Localization and Mapping (SLAM) in challenging environments. SLAM is one of the key enabling technologies for… (more)

▼ This dissertation addresses the problem of real-time Simultaneous Localization and Mapping (SLAM) in challenging environments. SLAM is one of the key enabling technologies for autonomous robots to navigate in unknown environments by processing information on their on-board computational units. In particular, we study the exploration of challenging GPS-denied underwater environments to enable a wide range of robotic applications, including historical studies, health monitoring of coral reefs, underwater infrastructure inspection e.g., bridges, hydroelectric dams, water supply systems, and oil rigs. Mapping underwater structures is important in several fields, such as marine archaeology, Search and Rescue (SaR), resource management, hydrogeology, and speleology. However, due to the highly unstructured nature of such environments, navigation by human divers could be extremely dangerous, tedious, and labor intensive. Hence, employing an underwater robot is an excellent fit to build the map of the environment while simultaneously localizing itself in the map. The main contribution of this dissertation is the design and development of a real-time robust SLAM algorithm for small and large scale underwater environments. SVIn – a novel tightly-coupled keyframe-based non-linear optimization framework fusing Sonar, Visual, Inertial and water depth information with robust initialization, loop-closing, and relocalization capabilities has been presented. Introducing acoustic range information to aid the visual data, shows improved reconstruction and localization. The availability of depth information from water pressure enables a robust initialization and refines the scale factor, as well as assists to reduce the drift for the tightly-coupled integration. The complementary characteristics of these sensing v modalities provide accurate and robust localization in unstructured environments with low visibility and low visual features – as such make them the ideal choice for underwater navigation. The proposed system has been successfully tested and validated in both benchmark datasets and numerous real world scenarios. It has also been used for planning for underwater robot in the presence of obstacles. Experimental results on datasets collected with a custom-made underwater sensor suite and an autonomous underwater vehicle (AUV) Aqua2 in challenging underwater environments with poor visibility, demonstrate performance never achieved before in terms of accuracy and robustness. To aid the sparse reconstruction, a contour-based reconstruction approach utilizing the well defined edges between the well lit area and darkness has been developed. In particular, low lighting conditions, or even complete absence of natural light inside caves, results in strong lighting variations, e.g., the cone of the artificial video light intersecting underwater structures and the shadow contours. The proposed method utilizes these contours to provide additional features, resulting into a denser 3D point cloud than the usual point clouds from a… Advisors/Committee Members: Ioannis Rekleitis.

Subjects/Keywords: computer vision; Robotics; sensor fusion; SLAM

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Rahman, S. (2020). A Multi-Sensor Fusion-Based Underwater Slam System. (Doctoral Dissertation). University of South Carolina. Retrieved from https://scholarcommons.sc.edu/etd/5987

Chicago Manual of Style (16^th Edition):

Rahman, Sharmin. “A Multi-Sensor Fusion-Based Underwater Slam System.” 2020. Doctoral Dissertation, University of South Carolina. Accessed February 27, 2021. https://scholarcommons.sc.edu/etd/5987.

MLA Handbook (7^th Edition):

Rahman, Sharmin. “A Multi-Sensor Fusion-Based Underwater Slam System.” 2020. Web. 27 Feb 2021.

Vancouver:

Rahman S. A Multi-Sensor Fusion-Based Underwater Slam System. [Internet] [Doctoral dissertation]. University of South Carolina; 2020. [cited 2021 Feb 27]. Available from: https://scholarcommons.sc.edu/etd/5987.

Council of Science Editors:

Rahman S. A Multi-Sensor Fusion-Based Underwater Slam System. [Doctoral Dissertation]. University of South Carolina; 2020. Available from: https://scholarcommons.sc.edu/etd/5987

University of Kentucky

18. Zhao, Jian. Camera Planning and Fusion in a Heterogeneous Camera Network.

Degree: 2011, University of Kentucky

URL: https://uknowledge.uky.edu/ece_etds/2

► Wide-area camera networks are becoming more and more common. They have widerange of commercial and military applications from video surveillance to smart home and from… (more)

▼ Wide-area camera networks are becoming more and more common. They have widerange of commercial and military applications from video surveillance to smart home and from traffic monitoring to anti-terrorism. The design of such a camera network is a challenging problem due to the complexity of the environment, self and mutual occlusion of moving objects, diverse sensor properties and a myriad of performance metrics for different applications. In this dissertation, we consider two such challenges: camera planing and camera fusion. Camera planning is to determine the optimal number and placement of cameras for a target cost function. Camera fusion describes the task of combining images collected by heterogenous cameras in the network to extract information pertinent to a target application. I tackle the camera planning problem by developing a new unified framework based on binary integer programming (BIP) to relate the network design parameters and the performance goals of a variety of camera network tasks. Most of the BIP formulations are NP hard problems and various approximate algorithms have been proposed in the literature. In this dissertation, I develop a comprehensive framework in comparing the entire spectrum of approximation algorithms from Greedy, Markov Chain Monte Carlo (MCMC) to various relaxation techniques. The key contribution is to provide not only a generic formulation of the camera planning problem but also novel approaches to adapt the formulation to powerful approximation schemes including Simulated Annealing (SA) and Semi-Definite Program (SDP). The accuracy, efficiency and scalability of each technique are analyzed and compared in depth. Extensive experimental results are provided to illustrate the strength and weakness of each method. The second problem of heterogeneous camera fusion is a very complex problem. Information can be fused at different levels from pixel or voxel to semantic objects, with large variation in accuracy, communication and computation costs. My focus is on the geometric transformation of shapes between objects observed at different camera planes. This so-called the geometric fusion approach usually provides the most reliable fusion approach at the expense of high computation and communication costs. To tackle the complexity, a hierarchy of camera models with different levels of complexity was proposed to balance the effectiveness and efficiency of the camera network operation. Then different calibration and registration methods are proposed for each camera model. At last, I provide two specific examples to demonstrate the effectiveness of the model: 1)a fusion system to improve the segmentation of human body in a camera network consisted of thermal and regular visible light cameras and 2) a view dependent rendering system by combining the information from depth and regular cameras to collecting the scene information and generating new views in real time.

Subjects/Keywords: Sensor Planning; Camera Placement; Sensor Fusion; Human Segmentation; Multi-camera Fusion; Electrical and Computer Engineering

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APA (6^th Edition):

Zhao, J. (2011). Camera Planning and Fusion in a Heterogeneous Camera Network. (Doctoral Dissertation). University of Kentucky. Retrieved from https://uknowledge.uky.edu/ece_etds/2

Chicago Manual of Style (16^th Edition):

Zhao, Jian. “Camera Planning and Fusion in a Heterogeneous Camera Network.” 2011. Doctoral Dissertation, University of Kentucky. Accessed February 27, 2021. https://uknowledge.uky.edu/ece_etds/2.

MLA Handbook (7^th Edition):

Zhao, Jian. “Camera Planning and Fusion in a Heterogeneous Camera Network.” 2011. Web. 27 Feb 2021.

Vancouver:

Zhao J. Camera Planning and Fusion in a Heterogeneous Camera Network. [Internet] [Doctoral dissertation]. University of Kentucky; 2011. [cited 2021 Feb 27]. Available from: https://uknowledge.uky.edu/ece_etds/2.

Council of Science Editors:

Zhao J. Camera Planning and Fusion in a Heterogeneous Camera Network. [Doctoral Dissertation]. University of Kentucky; 2011. Available from: https://uknowledge.uky.edu/ece_etds/2

Michigan Technological University

19. Demars, Casey D. Target detection, tracking, and localization using multi-spectral image fusion and RF Doppler differentials.

Degree: PhD, Department of Electrical and Computer Engineering, 2018, Michigan Technological University

URL: https://digitalcommons.mtu.edu/etdr/720

► It is critical for defense and security applications to have a high probability of detection and low false alarm rate while operating over a… (more)

▼ It is critical for defense and security applications to have a high probability of detection and low false alarm rate while operating over a wide variety of conditions. Sensor fusion, which is the the process of combining data from two or more sensors, has been utilized to improve the performance of a system by exploiting the strengths of each sensor. This dissertation presents algorithms to fuse multi-sensor data that improves system performance by increasing detection rates, lowering false alarms, and improving track performance. Furthermore, this dissertation presents a framework for comparing algorithm error for image registration which is a critical pre-processing step for multi-spectral image fusion. First, I present an algorithm to improve detection and tracking performance for moving targets in a cluttered urban environment by fusing foreground maps from multi-spectral imagery. Most research in image fusion consider visible and long-wave infrared bands; I examine these bands along with near infrared and mid-wave infrared. To localize and track a particular target of interest, I present an algorithm to fuse output from the multi-spectral image tracker with a constellation of RF sensors measuring a specific cellular emanation. The fusion algorithm matches the Doppler differential from the RF sensors with the theoretical Doppler Differential of the video tracker output by selecting the sensor pair that minimizes the absolute difference or root-mean-square difference. Finally, a framework to quantify shift-estimation error for both area- and feature-based algorithms is presented. By exploiting synthetically generated visible and long-wave infrared imagery, error metrics are computed and compared for a number of area- and feature-based shift estimation algorithms. A number of key results are presented in this dissertation. The multi-spectral image tracker improves the location accuracy of the algorithm while improving the detection rate and lowering false alarms for most spectral bands. All 12 moving targets were tracked through the video sequence with only one lost track that was later recovered. Targets from the multi-spectral tracking algorithm were correctly associated with their corresponding cellular emanation for all targets at lower measurement uncertainty using the root-mean-square difference while also having a high confidence ratio for selecting the true target from background targets. For the area-based algorithms and the synthetic air-field image pair, the DFT and ECC algorithms produces sub-pixel shift-estimation error in regions such as shadows and high contrast painted line regions. The edge orientation feature descriptors increase the number of sub-field estimates while improving the shift-estimation error compared to the Lowe descriptor. Advisors/Committee Members: Dr. Michael C. Roggemann.

Subjects/Keywords: Sensor fusion; image processing; data fusion; target tracking; Signal Processing

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APA (6^th Edition):

Demars, C. D. (2018). Target detection, tracking, and localization using multi-spectral image fusion and RF Doppler differentials. (Doctoral Dissertation). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/720

Chicago Manual of Style (16^th Edition):

Demars, Casey D. “Target detection, tracking, and localization using multi-spectral image fusion and RF Doppler differentials.” 2018. Doctoral Dissertation, Michigan Technological University. Accessed February 27, 2021. https://digitalcommons.mtu.edu/etdr/720.

MLA Handbook (7^th Edition):

Demars, Casey D. “Target detection, tracking, and localization using multi-spectral image fusion and RF Doppler differentials.” 2018. Web. 27 Feb 2021.

Vancouver:

Demars CD. Target detection, tracking, and localization using multi-spectral image fusion and RF Doppler differentials. [Internet] [Doctoral dissertation]. Michigan Technological University; 2018. [cited 2021 Feb 27]. Available from: https://digitalcommons.mtu.edu/etdr/720.

Council of Science Editors:

Demars CD. Target detection, tracking, and localization using multi-spectral image fusion and RF Doppler differentials. [Doctoral Dissertation]. Michigan Technological University; 2018. Available from: https://digitalcommons.mtu.edu/etdr/720

Carnegie Mellon University

20. Han, Jun. Advantages and Risks of Sensing for Cyber-Physical Security.

Degree: 2018, Carnegie Mellon University

URL: http://repository.cmu.edu/dissertations/1161

► With the the emergence of the Internet-of-Things (IoT) and Cyber-Physical Systems (CPS), modern computing is now transforming from residing only in the cyber domain to… (more)

Subjects/Keywords: Context-based Pairing; IoT Security; Sensor Fusion; Sensor Security

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Han, J. (2018). Advantages and Risks of Sensing for Cyber-Physical Security. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/1161

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Han, Jun. “Advantages and Risks of Sensing for Cyber-Physical Security.” 2018. Thesis, Carnegie Mellon University. Accessed February 27, 2021. http://repository.cmu.edu/dissertations/1161.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Han, Jun. “Advantages and Risks of Sensing for Cyber-Physical Security.” 2018. Web. 27 Feb 2021.

Vancouver:

Han J. Advantages and Risks of Sensing for Cyber-Physical Security. [Internet] [Thesis]. Carnegie Mellon University; 2018. [cited 2021 Feb 27]. Available from: http://repository.cmu.edu/dissertations/1161.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Han J. Advantages and Risks of Sensing for Cyber-Physical Security. [Thesis]. Carnegie Mellon University; 2018. Available from: http://repository.cmu.edu/dissertations/1161

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

21. Tonderski, Adam. Sensor Fusion with Failure Robustness A Deep Learning 3D Object Detection Architecture .

Degree: Chalmers tekniska högskola / Institutionen för fysik, 2019, Chalmers University of Technology

URL: http://hdl.handle.net/20.500.12380/300780

► Autonomous Driving is the task of navigating a vehicle without driver interaction. This requires accurate perception of the surroundings, which includes three dimensional object detection.… (more)

Subjects/Keywords: Deep Learning; Sensor Fusion; Object Detection; Sensor Failure; KITTI

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Tonderski, A. (2019). Sensor Fusion with Failure Robustness A Deep Learning 3D Object Detection Architecture . (Thesis). Chalmers University of Technology. Retrieved from http://hdl.handle.net/20.500.12380/300780

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Tonderski, Adam. “Sensor Fusion with Failure Robustness A Deep Learning 3D Object Detection Architecture .” 2019. Thesis, Chalmers University of Technology. Accessed February 27, 2021. http://hdl.handle.net/20.500.12380/300780.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Tonderski, Adam. “Sensor Fusion with Failure Robustness A Deep Learning 3D Object Detection Architecture .” 2019. Web. 27 Feb 2021.

Vancouver:

Tonderski A. Sensor Fusion with Failure Robustness A Deep Learning 3D Object Detection Architecture . [Internet] [Thesis]. Chalmers University of Technology; 2019. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/20.500.12380/300780.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tonderski A. Sensor Fusion with Failure Robustness A Deep Learning 3D Object Detection Architecture . [Thesis]. Chalmers University of Technology; 2019. Available from: http://hdl.handle.net/20.500.12380/300780

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

22. de Vries, Maarten (author). Multi-Rate Unscented Kalman Filtering for Pose Estimation: Using a car-like vehicle-platform.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:e5d2506a-df25-4187-8ffa-10ffd2c819c6

►

Pose estimation through fusion of GNSS with secondary sensors has long been an established field. With the developments surrounding autonomous navigation over the past decade… (more)

Subjects/Keywords: GNSS; Kalman Filter; Unscented Kalman; Pose estimation; sensor fusion; Multi-Rate; IMU sensor fusion; Vehicle-sensor; Protocol

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

de Vries, M. (. (2019). Multi-Rate Unscented Kalman Filtering for Pose Estimation: Using a car-like vehicle-platform. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:e5d2506a-df25-4187-8ffa-10ffd2c819c6

Chicago Manual of Style (16^th Edition):

de Vries, Maarten (author). “Multi-Rate Unscented Kalman Filtering for Pose Estimation: Using a car-like vehicle-platform.” 2019. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:e5d2506a-df25-4187-8ffa-10ffd2c819c6.

MLA Handbook (7^th Edition):

de Vries, Maarten (author). “Multi-Rate Unscented Kalman Filtering for Pose Estimation: Using a car-like vehicle-platform.” 2019. Web. 27 Feb 2021.

Vancouver:

de Vries M(. Multi-Rate Unscented Kalman Filtering for Pose Estimation: Using a car-like vehicle-platform. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:e5d2506a-df25-4187-8ffa-10ffd2c819c6.

Council of Science Editors:

de Vries M(. Multi-Rate Unscented Kalman Filtering for Pose Estimation: Using a car-like vehicle-platform. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:e5d2506a-df25-4187-8ffa-10ffd2c819c6

23. Antigny, Nicolas. Estimation continue de la pose d'un équipement tenu en main par fusion des données visio-inertielles pour les applications de navigation piétonne en milieux urbains : Continuous pose estimation of handheld device by fusion of visio-inertial data for pedestrian navigation applications in urban environments.

Degree: Docteur es, Signal, Image, Vision, 2018, Ecole centrale de Nantes

URL: http://www.theses.fr/2018ECDN0027

►

Pour assister la navigation piétonne dans les espaces urbains et intérieurs, une estimation précise de la pose (i.e. la position 3D et l'orientation3D) d'un équipement… (more)

▼

Pour assister la navigation piétonne dans les espaces urbains et intérieurs, une estimation précise de la pose (i.e. la position 3D et l'orientation3D) d'un équipement tenu en main constitue un point essentiel dans le développement d'outils d'aide à la mobilité (e.g. applications de réalité augmentée). Dans l'hypothèse où le piéton n'est équipé que d'appareils grand public, l'estimation de la pose est limitée à l'utilisation de capteurs à faible coût intégrés dans ces derniers (i.e. un récepteur GNSS, une unité de mesure inertielle et magnétique et une caméra monoculaire). De plus, les espaces urbains et intérieurs, comprenant des bâtiments proches et des éléments ferromagnétiques, constituent des zones difficiles pour la localisation et l'estimation de la pose lors de grands déplacements piétons.Cependant, le développement récent et la mise à disposition d'informations contenues dans des Systèmes d'Information Géographiques 3D constituent une nouvelle source de données exploitable pour la localisation et l'estimation de la pose. Pour relever ces défis, cette thèse propose différentes solutions pour améliorer la localisation et l'estimation de la pose des équipements tenus en main par le piéton lors de ses déplacements en espaces urbains et intérieurs. Les solutions proposées intègrent l'estimation de l'attitude basée inertielle et magnétique, l'odométrie visuelle monoculaire mise à l'échelle grâce à l'estimation des déplacements du piéton, l'estimation absolue de la pose basée sur la reconnaissance d'objets SIG 3D parfaitement connus et la mise à jour en position de la navigation à l'estime du piéton.Toutes ces solutions s'intègrent dans un processus de fusion permettant d'améliorer la précision de la localisation et d'estimer en continu une pose qualifiée de l'appareil tenu en main.Cette qualification est nécessaire à la mise en place d'un affichage en réalité augmentée sur site. Pour évaluer les solutions proposées, des données expérimentales ont été recueillies au cours de déplacements piétons dans un espace urbain avec des objets de référence et des passages intérieurs.

To support pedestrian navigation in urban and indoor spaces, an accurate pose estimate (i.e. 3Dposition and 3D orientation) of an equipment held inhand constitutes an essential point in the development of mobility assistance tools (e.g.Augmented Reality applications). On the assumption that the pedestrian is only equipped with general public devices, the pose estimation is restricted to the use of low-cost sensors embedded in the latter (i.e. an Inertial and Magnetic Measurement Unit and a monocular camera). In addition, urban and indoor spaces, comprising closely-spaced buildings and ferromagnetic elements,constitute challenging areas for localization and sensor pose estimation during large pedestrian displacements.However, the recent development and provision of data contained in 3D Geographical Information System constitutes a new wealth of data usable for localization and pose estimation.To address these challenges, this thesis proposes…

Advisors/Committee Members: Renaudin, Valérie (thesis director).

Subjects/Keywords: Navigation piétonne; Fusion de données; Réalité augmentée; Pedestrian navigation; Sensor fusion; Augmented reality; 004

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Antigny, N. (2018). Estimation continue de la pose d'un équipement tenu en main par fusion des données visio-inertielles pour les applications de navigation piétonne en milieux urbains : Continuous pose estimation of handheld device by fusion of visio-inertial data for pedestrian navigation applications in urban environments. (Doctoral Dissertation). Ecole centrale de Nantes. Retrieved from http://www.theses.fr/2018ECDN0027

Chicago Manual of Style (16^th Edition):

Antigny, Nicolas. “Estimation continue de la pose d'un équipement tenu en main par fusion des données visio-inertielles pour les applications de navigation piétonne en milieux urbains : Continuous pose estimation of handheld device by fusion of visio-inertial data for pedestrian navigation applications in urban environments.” 2018. Doctoral Dissertation, Ecole centrale de Nantes. Accessed February 27, 2021. http://www.theses.fr/2018ECDN0027.

MLA Handbook (7^th Edition):

Antigny, Nicolas. “Estimation continue de la pose d'un équipement tenu en main par fusion des données visio-inertielles pour les applications de navigation piétonne en milieux urbains : Continuous pose estimation of handheld device by fusion of visio-inertial data for pedestrian navigation applications in urban environments.” 2018. Web. 27 Feb 2021.

Vancouver:

Antigny N. Estimation continue de la pose d'un équipement tenu en main par fusion des données visio-inertielles pour les applications de navigation piétonne en milieux urbains : Continuous pose estimation of handheld device by fusion of visio-inertial data for pedestrian navigation applications in urban environments. [Internet] [Doctoral dissertation]. Ecole centrale de Nantes; 2018. [cited 2021 Feb 27]. Available from: http://www.theses.fr/2018ECDN0027.

Council of Science Editors:

Antigny N. Estimation continue de la pose d'un équipement tenu en main par fusion des données visio-inertielles pour les applications de navigation piétonne en milieux urbains : Continuous pose estimation of handheld device by fusion of visio-inertial data for pedestrian navigation applications in urban environments. [Doctoral Dissertation]. Ecole centrale de Nantes; 2018. Available from: http://www.theses.fr/2018ECDN0027

Delft University of Technology

24. Bootsma, B.G.N. (author). Learning Interactively to Resolve Ambiguity in Sensor Policy Fusion for Robot.

Degree: 2021, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:1f4a04fe-f57b-46d2-87dd-2a9e1c7d30e4

►

This work applies interactive imitation learning for the navigation of a mobile robot. The algorithm"Learning Interactively to Resolve Ambiguity in Sensor Policy Fusion" (LIRA-SPF) is… (more)

Subjects/Keywords: Interactive Imitation Learning; Navigation; End-to-End; Robot; Collision Avoidance; Sensor fusion; Policy fusion

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Bootsma, B. G. N. (. (2021). Learning Interactively to Resolve Ambiguity in Sensor Policy Fusion for Robot. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:1f4a04fe-f57b-46d2-87dd-2a9e1c7d30e4

Chicago Manual of Style (16^th Edition):

Bootsma, B G N (author). “Learning Interactively to Resolve Ambiguity in Sensor Policy Fusion for Robot.” 2021. Masters Thesis, Delft University of Technology. Accessed February 27, 2021. http://resolver.tudelft.nl/uuid:1f4a04fe-f57b-46d2-87dd-2a9e1c7d30e4.

MLA Handbook (7^th Edition):

Bootsma, B G N (author). “Learning Interactively to Resolve Ambiguity in Sensor Policy Fusion for Robot.” 2021. Web. 27 Feb 2021.

Vancouver:

Bootsma BGN(. Learning Interactively to Resolve Ambiguity in Sensor Policy Fusion for Robot. [Internet] [Masters thesis]. Delft University of Technology; 2021. [cited 2021 Feb 27]. Available from: http://resolver.tudelft.nl/uuid:1f4a04fe-f57b-46d2-87dd-2a9e1c7d30e4.

Council of Science Editors:

Bootsma BGN(. Learning Interactively to Resolve Ambiguity in Sensor Policy Fusion for Robot. [Masters Thesis]. Delft University of Technology; 2021. Available from: http://resolver.tudelft.nl/uuid:1f4a04fe-f57b-46d2-87dd-2a9e1c7d30e4

25. Dia, Roxana. Towards Environment Perception using Integer Arithmetic for Embedded Application : Vers une perception de l'environnement en utilisant l'arithmétique entière pour une application sur systèmes embarqués.

Degree: Docteur es, Mathématiques et informatique, 2020, Université Grenoble Alpes

URL: http://www.theses.fr/2020GRALM038

►

Le principal inconvénient de l'utilisation de représentations basées sur la grille pour SLAM et pour la localisation globale est la complexité de calcul exponentielle requise… (more)

▼

Le principal inconvénient de l'utilisation de représentations basées sur la grille pour SLAM et pour la localisation globale est la complexité de calcul exponentielle requise en termes de taille de grille (de la carte et des cartes de pose). La taille de grille requise pour modéliser l'environnement entourant un robot ou un véhicule peut être de l'ordre de milliers de millions de cellules. Par exemple, un espace 2D de forme carrée de taille 100 m × 100 m, avec une taille de cellule de 10 cm est modélisé avec une grille de 1 million de cellules. Si nous incluons une hauteur de 2 m pour représenter la troisième dimension, 20 millions de cellules sont nécessaires. Par conséquent, les approches SLAM classiques basées sur une grille et de localisation globale nécessitent une unité de calcul parallèle afin de répondre à la latence imposée par les normes de sécurité. Un tel calcul est généralement effectué sur des postes de travail intégrant des unités de traitement graphique (GPU) et / ou des processeurs haut de gamme. Cependant, les véhicules autonomes ne peuvent pas gérer de telles plateformes pour des raisons de coût et de problèmes de certification. De plus, ces plates-formes nécessitent une consommation d'énergie élevée qui ne peut pas correspondre à la source d'énergie limitée disponible dans certains robots. Les plates-formes matérielles intégrées sont couramment utilisées comme solution alternative dans les applications automobiles. Ces plateformes répondent aux contraintes de faible coût, de faible puissance et de petit espace. De plus, certains d'entre eux sont certifiés automobiles1, suivant la norme ISO26262. Cependant, la plupart d'entre eux ne sont pas équipés d'une unité à virgule flottante, ce qui limite les performances de calcul.L'équipe du projet sigma-fusion du laboratoire LIALP du CEA-Leti a développé une méthode de perception basée sur des nombres entiers adaptée aux appareils embarqués. Cette méthode permet de construire une grille d'occupation via la fusion bayésienne en utilisant uniquement l'arithmétique entière, d'où son "embarquabilité" sur des plateformes informatiques embarquées, sans unité à virgule flottante. Ceci constitue la contribution majeure de la thèse de doctorat de Tiana Rakotovao [Rakotovao Andriamahefa 2017].L'objectif de la présente thèse est d'étendre le cadre de perception des nombres entiers au SLAM et aux problèmes de localisation globale, offrant ainsi des solutions «embarquables» sur les systèmes embarqués.

The main drawback of using grid-based representations for SLAM and for global localization is the required exponential computational complexity in terms of the grid size (of the map and the pose maps). The required grid size for modeling the environment surrounding a robot or of a vehicle can be in the order of thousands of millions of cells. For instance, a 2D square-shape space of size 100m × 100m, with a cell size of 10cm is modelled with a grid of 1 million cells. If we include a 2m of height to represent the third dimension, 20 millions of cells are required.…

Advisors/Committee Members: Lesecq, Suzanne (thesis director), Parissis, Ioannis (thesis director).

Subjects/Keywords: Cartographie et Localisation Simultanées; Fusion entière; Capteur; Integer Fusion; Simultaneous localization and mapping; Sensor; 510

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Dia, R. (2020). Towards Environment Perception using Integer Arithmetic for Embedded Application : Vers une perception de l'environnement en utilisant l'arithmétique entière pour une application sur systèmes embarqués. (Doctoral Dissertation). Université Grenoble Alpes. Retrieved from http://www.theses.fr/2020GRALM038

Chicago Manual of Style (16^th Edition):

Dia, Roxana. “Towards Environment Perception using Integer Arithmetic for Embedded Application : Vers une perception de l'environnement en utilisant l'arithmétique entière pour une application sur systèmes embarqués.” 2020. Doctoral Dissertation, Université Grenoble Alpes. Accessed February 27, 2021. http://www.theses.fr/2020GRALM038.

MLA Handbook (7^th Edition):

Dia, Roxana. “Towards Environment Perception using Integer Arithmetic for Embedded Application : Vers une perception de l'environnement en utilisant l'arithmétique entière pour une application sur systèmes embarqués.” 2020. Web. 27 Feb 2021.

Vancouver:

Dia R. Towards Environment Perception using Integer Arithmetic for Embedded Application : Vers une perception de l'environnement en utilisant l'arithmétique entière pour une application sur systèmes embarqués. [Internet] [Doctoral dissertation]. Université Grenoble Alpes; 2020. [cited 2021 Feb 27]. Available from: http://www.theses.fr/2020GRALM038.

Council of Science Editors:

Dia R. Towards Environment Perception using Integer Arithmetic for Embedded Application : Vers une perception de l'environnement en utilisant l'arithmétique entière pour une application sur systèmes embarqués. [Doctoral Dissertation]. Université Grenoble Alpes; 2020. Available from: http://www.theses.fr/2020GRALM038

University of Manchester

26. Zebin, Tahmina. Wearable Inertial Multi-Sensor System for Physical Activity Analysis and Classification with Machine Learning Algorithms.

Degree: 2018, University of Manchester

URL: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314312

►

Wearable sensors such as inertial measurement units (IMUs) have been widely used to measure the quality of physical activities during daily living in healthy and… (more)

▼

Wearable sensors such as inertial measurement units (IMUs) have been widely used to measure the quality of physical activities during daily living in healthy and people with movement disorders through activity classification. These sensors have the potential to provide valuable information of the movement during the activities of daily living (ADL), such as walking, sitting down, and standing up, which could help clinicians to monitor rehabilitation and therapeutic interventions. However, high accuracy in the detection and segmentation of these activities is necessary for proper evaluation of the quality of the performance for a given activity. In this research, we devised a wearable inertial sensor system to measure physical activities and to calculate spatio-temporal gait parameters. We presented advanced signal processing and machine learning algorithms for accurate measurement of gait parameters from the sensor values. We implemented a fusion factor based method to deal with the accumulated drift and integration noise in inertial sensor data in an adaptive manner. We further implemented a quaternion sensor fusion algorithm for joint angle measurement and achieved less noisy values for static and dynamic joint angles with a fourth order Runge-Kutta method. For classification of daily life activities,we rigorously analyzed and handcrafted sixty-six statistical, and frequency domain features from the accelerometer and gyroscope time-series. This feature set was then used to train several state-ofthe- art and novel classifiers. We designed and trained Decision trees, Support Vector Machines, k-nearest neighbour, Ensemble algorithms during our experiments. Our investigation revealed that support vector machine classifier with quadratic kernel and a bagged ensemble classifier met the required value of accuracy of above 90%. Since hand-crafting of features require substantial domain knowledge, we devised a novel deep convolutional neural network to extract and select the features from the raw sensor signals automatically. For this, we proposed and implemented a CNN with dropout regularization and batch normalization, achieving a 96.7% accuracy proving the superiority of automatically learned features over hand-crafted ones.

Dataset, Demo and codes at https://github.com/TZebin/Thesis-Supporting-Files

Advisors/Committee Members: SCULLY, PATRICIA PJ, Ozanyan, Krikor, Scully, Patricia.

Subjects/Keywords: Wearable Sensor; Machine Learning; Convolutional Neural Network; Sensor Fusion; Activity Recognition; Gait Analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Zebin, T. (2018). Wearable Inertial Multi-Sensor System for Physical Activity Analysis and Classification with Machine Learning Algorithms. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314312

Chicago Manual of Style (16^th Edition):

Zebin, Tahmina. “Wearable Inertial Multi-Sensor System for Physical Activity Analysis and Classification with Machine Learning Algorithms.” 2018. Doctoral Dissertation, University of Manchester. Accessed February 27, 2021. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314312.

MLA Handbook (7^th Edition):

Zebin, Tahmina. “Wearable Inertial Multi-Sensor System for Physical Activity Analysis and Classification with Machine Learning Algorithms.” 2018. Web. 27 Feb 2021.

Vancouver:

Zebin T. Wearable Inertial Multi-Sensor System for Physical Activity Analysis and Classification with Machine Learning Algorithms. [Internet] [Doctoral dissertation]. University of Manchester; 2018. [cited 2021 Feb 27]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314312.

Council of Science Editors:

Zebin T. Wearable Inertial Multi-Sensor System for Physical Activity Analysis and Classification with Machine Learning Algorithms. [Doctoral Dissertation]. University of Manchester; 2018. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:314312

University of Colorado

27. Iglesias Echevarria, David I. Cooperative Robot Localization Using Event-Triggered Estimation.

Degree: MS, 2017, University of Colorado

URL: https://scholar.colorado.edu/asen_gradetds/206

► It is known that multiple robot systems that need to cooperate to perform certain activities or tasks incur in high energy costs that hinder their… (more)

Subjects/Keywords: localization; mobile robotics; sensor fusion; state estimation; statistical inference; wireless sensor networks; Aerospace Engineering; Robotics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Iglesias Echevarria, D. I. (2017). Cooperative Robot Localization Using Event-Triggered Estimation. (Masters Thesis). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/206

Chicago Manual of Style (16^th Edition):

Iglesias Echevarria, David I. “Cooperative Robot Localization Using Event-Triggered Estimation.” 2017. Masters Thesis, University of Colorado. Accessed February 27, 2021. https://scholar.colorado.edu/asen_gradetds/206.

MLA Handbook (7^th Edition):

Iglesias Echevarria, David I. “Cooperative Robot Localization Using Event-Triggered Estimation.” 2017. Web. 27 Feb 2021.

Vancouver:

Iglesias Echevarria DI. Cooperative Robot Localization Using Event-Triggered Estimation. [Internet] [Masters thesis]. University of Colorado; 2017. [cited 2021 Feb 27]. Available from: https://scholar.colorado.edu/asen_gradetds/206.

Council of Science Editors:

Iglesias Echevarria DI. Cooperative Robot Localization Using Event-Triggered Estimation. [Masters Thesis]. University of Colorado; 2017. Available from: https://scholar.colorado.edu/asen_gradetds/206

University of Colorado

28. Iglesias Echevarria, David I. Cooperative Robot Localization Using Event-Triggered Estimation.

Degree: MS, 2017, University of Colorado

URL: https://scholar.colorado.edu/asen_gradetds/185

► It is known that multiple robot systems that need to cooperate to perform certain activities or tasks incur in high energy costs that hinder their… (more)

Subjects/Keywords: localization; mobile robotics; sensor fusion; state estimation; statistical inference; wireless sensor networks; Aerospace Engineering; Robotics

Record Details Similar Records Cite « Share

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Iglesias Echevarria, D. I. (2017). Cooperative Robot Localization Using Event-Triggered Estimation. (Masters Thesis). University of Colorado. Retrieved from https://scholar.colorado.edu/asen_gradetds/185

Chicago Manual of Style (16^th Edition):

Iglesias Echevarria, David I. “Cooperative Robot Localization Using Event-Triggered Estimation.” 2017. Masters Thesis, University of Colorado. Accessed February 27, 2021. https://scholar.colorado.edu/asen_gradetds/185.

MLA Handbook (7^th Edition):

Iglesias Echevarria, David I. “Cooperative Robot Localization Using Event-Triggered Estimation.” 2017. Web. 27 Feb 2021.

Vancouver:

Iglesias Echevarria DI. Cooperative Robot Localization Using Event-Triggered Estimation. [Internet] [Masters thesis]. University of Colorado; 2017. [cited 2021 Feb 27]. Available from: https://scholar.colorado.edu/asen_gradetds/185.

Council of Science Editors:

Iglesias Echevarria DI. Cooperative Robot Localization Using Event-Triggered Estimation. [Masters Thesis]. University of Colorado; 2017. Available from: https://scholar.colorado.edu/asen_gradetds/185

University of Illinois – Chicago

29. Khan, Nishat Anjum. Multi-Sensor Preprocessing for Traffic Light Detection.

Degree: 2017, University of Illinois – Chicago

URL: http://hdl.handle.net/10027/22181

► With the exponential growth of smartphone usage and its computational capability, there is an opportunity today to build a usable navigation system for the visually… (more)

Subjects/Keywords: Image Processing; Traffic Lights; Walk Signs; Pedestrian Navigation; Video Analytics; Sensor Fusion; Inertial Sensor

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Khan, N. A. (2017). Multi-Sensor Preprocessing for Traffic Light Detection. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/22181

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Khan, Nishat Anjum. “Multi-Sensor Preprocessing for Traffic Light Detection.” 2017. Thesis, University of Illinois – Chicago. Accessed February 27, 2021. http://hdl.handle.net/10027/22181.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Khan, Nishat Anjum. “Multi-Sensor Preprocessing for Traffic Light Detection.” 2017. Web. 27 Feb 2021.

Vancouver:

Khan NA. Multi-Sensor Preprocessing for Traffic Light Detection. [Internet] [Thesis]. University of Illinois – Chicago; 2017. [cited 2021 Feb 27]. Available from: http://hdl.handle.net/10027/22181.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Khan NA. Multi-Sensor Preprocessing for Traffic Light Detection. [Thesis]. University of Illinois – Chicago; 2017. Available from: http://hdl.handle.net/10027/22181

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Manchester

30. Zebin, Tahmina. Wearable inertial multi-sensor system for physical activity analysis and classification with machine learning algorithms.

Degree: PhD, 2018, University of Manchester

URL: https://www.research.manchester.ac.uk/portal/en/theses/wearable-inertial-multisensor-system-for-physical-activity-analysis-and-classification-with-machine-learning-algorithms(57df353c-e3e8-405b-bc8f-86c883554223).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.779579

► Wearable sensors such as inertial measurement units (IMUs) have been widely used to measure the quality of physical activities during daily living in healthy and… (more)

▼ Wearable sensors such as inertial measurement units (IMUs) have been widely used to measure the quality of physical activities during daily living in healthy and people with movement disorders through activity classification. These sensors have the potential to provide valuable information of the movement during the activities of daily living (ADL), such as walking, sitting down, and standing up, which could help clinicians to monitor rehabilitation and therapeutic interventions. However, high accuracy in the detection and segmentation of these activities is necessary for proper evaluation of the quality of the performance for a given activity. In this research, we devised a wearable inertial sensor system to measure physical activities and to calculate spatio-temporal gait parameters. We presented advanced signal processing and machine learning algorithms for accurate measurement of gait parameters from the sensor values. We implemented a fusion factor based method to deal with the accumulated drift and integration noise in inertial sensor data in an adaptive manner. We further implemented a quaternion sensor fusion algorithm for joint angle measurement and achieved less noisy values for static and dynamic joint angles with a fourth order Runge-Kutta method. For classification of daily life activities,we rigorously analyzed and handcrafted sixty-six statistical, and frequency domain features from the accelerometer and gyroscope time-series. This feature set was then used to train several state-ofthe- art and novel classifiers. We designed and trained Decision trees, Support Vector Machines, k-nearest neighbour, Ensemble algorithms during our experiments. Our investigation revealed that support vector machine classifier with quadratic kernel and a bagged ensemble classifier met the required value of accuracy of above 90%. Since hand-crafting of features require substantial domain knowledge, we devised a novel deep convolutional neural network to extract and select the features from the raw sensor signals automatically. For this, we proposed and implemented a CNN with dropout regularization and batch normalization, achieving a 96.7% accuracy proving the superiority of automatically learned features over hand-crafted ones.

Subjects/Keywords: Gait Analysis; Activity Recognition; Sensor Fusion; Machine Learning; Wearable Sensor; Convolutional Neural Network

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Zebin, T. (2018). Wearable inertial multi-sensor system for physical activity analysis and classification with machine learning algorithms. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/wearable-inertial-multisensor-system-for-physical-activity-analysis-and-classification-with-machine-learning-algorithms(57df353c-e3e8-405b-bc8f-86c883554223).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.779579

Chicago Manual of Style (16^th Edition):

Zebin, Tahmina. “Wearable inertial multi-sensor system for physical activity analysis and classification with machine learning algorithms.” 2018. Doctoral Dissertation, University of Manchester. Accessed February 27, 2021. https://www.research.manchester.ac.uk/portal/en/theses/wearable-inertial-multisensor-system-for-physical-activity-analysis-and-classification-with-machine-learning-algorithms(57df353c-e3e8-405b-bc8f-86c883554223).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.779579.

MLA Handbook (7^th Edition):

Zebin, Tahmina. “Wearable inertial multi-sensor system for physical activity analysis and classification with machine learning algorithms.” 2018. Web. 27 Feb 2021.

Vancouver:

Zebin T. Wearable inertial multi-sensor system for physical activity analysis and classification with machine learning algorithms. [Internet] [Doctoral dissertation]. University of Manchester; 2018. [cited 2021 Feb 27]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/wearable-inertial-multisensor-system-for-physical-activity-analysis-and-classification-with-machine-learning-algorithms(57df353c-e3e8-405b-bc8f-86c883554223).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.779579.

Council of Science Editors:

Zebin T. Wearable inertial multi-sensor system for physical activity analysis and classification with machine learning algorithms. [Doctoral Dissertation]. University of Manchester; 2018. Available from: https://www.research.manchester.ac.uk/portal/en/theses/wearable-inertial-multisensor-system-for-physical-activity-analysis-and-classification-with-machine-learning-algorithms(57df353c-e3e8-405b-bc8f-86c883554223).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.779579

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