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You searched for +publisher:"Penn State University" +contributor:("Sean Brennan, Dissertation Advisor/Co-Advisor"). Showing records 1 – 8 of 8 total matches.

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Penn State University

1. Robinson, Michael David. An Investigation of Fatality-Reducing Pedestrian Avoidance Algorithms for Autonomous Vehicles.

Degree: 2016, Penn State University

 As we approach the day when autonomous vehicles become commercially viable, questions about safety become more important than questions about feasibility. Historically, the literature on… (more)

Subjects/Keywords: Collision avoidance; pedestrian avoidance; vehicle modeling; Collision avoidance; pedestrian avoidance; vehicle modeling

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

APA (6th Edition):

Robinson, M. D. (2016). An Investigation of Fatality-Reducing Pedestrian Avoidance Algorithms for Autonomous Vehicles. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/12180mdr5254

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

Chicago Manual of Style (16th Edition):

Robinson, Michael David. “An Investigation of Fatality-Reducing Pedestrian Avoidance Algorithms for Autonomous Vehicles.” 2016. Thesis, Penn State University. Accessed April 19, 2021. https://submit-etda.libraries.psu.edu/catalog/12180mdr5254.

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

MLA Handbook (7th Edition):

Robinson, Michael David. “An Investigation of Fatality-Reducing Pedestrian Avoidance Algorithms for Autonomous Vehicles.” 2016. Web. 19 Apr 2021.

Vancouver:

Robinson MD. An Investigation of Fatality-Reducing Pedestrian Avoidance Algorithms for Autonomous Vehicles. [Internet] [Thesis]. Penn State University; 2016. [cited 2021 Apr 19]. Available from: https://submit-etda.libraries.psu.edu/catalog/12180mdr5254.

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

Council of Science Editors:

Robinson MD. An Investigation of Fatality-Reducing Pedestrian Avoidance Algorithms for Autonomous Vehicles. [Thesis]. Penn State University; 2016. Available from: https://submit-etda.libraries.psu.edu/catalog/12180mdr5254

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


Penn State University

2. Pentzer, Jesse Lorenzo. Utilization of ICR Kinematics in Estimation, Control, and Energy-Aware Mission Planning for Skid-Steer Vehicles.

Degree: 2014, Penn State University

 This dissertation provides details of work completed in the areas of skid-steer robot modeling, trajectory control, power modeling, and energy use prediction. The vast majority… (more)

Subjects/Keywords: ground robotics; robot performance; motion estimation; state estimation; skid-steer robotics; path planning

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APA (6th Edition):

Pentzer, J. L. (2014). Utilization of ICR Kinematics in Estimation, Control, and Energy-Aware Mission Planning for Skid-Steer Vehicles. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/23458

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

Chicago Manual of Style (16th Edition):

Pentzer, Jesse Lorenzo. “Utilization of ICR Kinematics in Estimation, Control, and Energy-Aware Mission Planning for Skid-Steer Vehicles.” 2014. Thesis, Penn State University. Accessed April 19, 2021. https://submit-etda.libraries.psu.edu/catalog/23458.

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

MLA Handbook (7th Edition):

Pentzer, Jesse Lorenzo. “Utilization of ICR Kinematics in Estimation, Control, and Energy-Aware Mission Planning for Skid-Steer Vehicles.” 2014. Web. 19 Apr 2021.

Vancouver:

Pentzer JL. Utilization of ICR Kinematics in Estimation, Control, and Energy-Aware Mission Planning for Skid-Steer Vehicles. [Internet] [Thesis]. Penn State University; 2014. [cited 2021 Apr 19]. Available from: https://submit-etda.libraries.psu.edu/catalog/23458.

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

Council of Science Editors:

Pentzer JL. Utilization of ICR Kinematics in Estimation, Control, and Energy-Aware Mission Planning for Skid-Steer Vehicles. [Thesis]. Penn State University; 2014. Available from: https://submit-etda.libraries.psu.edu/catalog/23458

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


Penn State University

3. Laftchiev, Emil Ivanov. Robust Dynamical Model-based Data Representations and Structuring of Time Series Data for In-sequence Localization.

Degree: 2014, Penn State University

 In the modern era there is an unprecedented ability to actuate via an increasingly cheaper array of actuators, and to sense through a growing, increasingly… (more)

Subjects/Keywords: Data Dimension Reduction; Stochastic Programming; Multi-dimensional Data Representation; In-Sequence Localization

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

APA (6th Edition):

Laftchiev, E. I. (2014). Robust Dynamical Model-based Data Representations and Structuring of Time Series Data for In-sequence Localization. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/23463

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

Chicago Manual of Style (16th Edition):

Laftchiev, Emil Ivanov. “Robust Dynamical Model-based Data Representations and Structuring of Time Series Data for In-sequence Localization.” 2014. Thesis, Penn State University. Accessed April 19, 2021. https://submit-etda.libraries.psu.edu/catalog/23463.

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

MLA Handbook (7th Edition):

Laftchiev, Emil Ivanov. “Robust Dynamical Model-based Data Representations and Structuring of Time Series Data for In-sequence Localization.” 2014. Web. 19 Apr 2021.

Vancouver:

Laftchiev EI. Robust Dynamical Model-based Data Representations and Structuring of Time Series Data for In-sequence Localization. [Internet] [Thesis]. Penn State University; 2014. [cited 2021 Apr 19]. Available from: https://submit-etda.libraries.psu.edu/catalog/23463.

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

Council of Science Editors:

Laftchiev EI. Robust Dynamical Model-based Data Representations and Structuring of Time Series Data for In-sequence Localization. [Thesis]. Penn State University; 2014. Available from: https://submit-etda.libraries.psu.edu/catalog/23463

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


Penn State University

4. Wahba, Mohamed. Factors affecting the repeatability of the fuel consumption of a heavy-duty truck on urban and highway roads.

Degree: 2019, Penn State University

 Trends in vehicle control show an increasing reliance on data aggregation and model-based predictive control to improve vehicle performance. The data and models that underly… (more)

Subjects/Keywords: V2I; Truck platoon

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

APA (6th Edition):

Wahba, M. (2019). Factors affecting the repeatability of the fuel consumption of a heavy-duty truck on urban and highway roads. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/16464mhw128

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

Chicago Manual of Style (16th Edition):

Wahba, Mohamed. “Factors affecting the repeatability of the fuel consumption of a heavy-duty truck on urban and highway roads.” 2019. Thesis, Penn State University. Accessed April 19, 2021. https://submit-etda.libraries.psu.edu/catalog/16464mhw128.

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

MLA Handbook (7th Edition):

Wahba, Mohamed. “Factors affecting the repeatability of the fuel consumption of a heavy-duty truck on urban and highway roads.” 2019. Web. 19 Apr 2021.

Vancouver:

Wahba M. Factors affecting the repeatability of the fuel consumption of a heavy-duty truck on urban and highway roads. [Internet] [Thesis]. Penn State University; 2019. [cited 2021 Apr 19]. Available from: https://submit-etda.libraries.psu.edu/catalog/16464mhw128.

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

Council of Science Editors:

Wahba M. Factors affecting the repeatability of the fuel consumption of a heavy-duty truck on urban and highway roads. [Thesis]. Penn State University; 2019. Available from: https://submit-etda.libraries.psu.edu/catalog/16464mhw128

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


Penn State University

5. Brown, Alexander Allen. Model-based Inclusion of Previewed Information for Lateral Vehicle State and Environment Estimation.

Degree: 2013, Penn State University

 This dissertation is concerned with the marriage of spatiotemporal preview as it is known in the controls literature with map-based guidance in a simple but… (more)

Subjects/Keywords: MODEL-BASED ESTIMATION; PREVIEW ESTIMATION; STATE ESTIMATION; VEHICLE DYNAMICS; AUTONOMOUS VEHICLES

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

APA (6th Edition):

Brown, A. A. (2013). Model-based Inclusion of Previewed Information for Lateral Vehicle State and Environment Estimation. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/18992

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

Chicago Manual of Style (16th Edition):

Brown, Alexander Allen. “Model-based Inclusion of Previewed Information for Lateral Vehicle State and Environment Estimation.” 2013. Thesis, Penn State University. Accessed April 19, 2021. https://submit-etda.libraries.psu.edu/catalog/18992.

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

MLA Handbook (7th Edition):

Brown, Alexander Allen. “Model-based Inclusion of Previewed Information for Lateral Vehicle State and Environment Estimation.” 2013. Web. 19 Apr 2021.

Vancouver:

Brown AA. Model-based Inclusion of Previewed Information for Lateral Vehicle State and Environment Estimation. [Internet] [Thesis]. Penn State University; 2013. [cited 2021 Apr 19]. Available from: https://submit-etda.libraries.psu.edu/catalog/18992.

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

Council of Science Editors:

Brown AA. Model-based Inclusion of Previewed Information for Lateral Vehicle State and Environment Estimation. [Thesis]. Penn State University; 2013. Available from: https://submit-etda.libraries.psu.edu/catalog/18992

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


Penn State University

6. Virani, Nurali. Learning Data-driven Models for Decision-making in Intelligent Physical Systems.

Degree: 2017, Penn State University

 Intelligent physical systems use machine learning for a variety of tasks from health monitoring to control. As the dependence on autonomous decision-making agents increases, it… (more)

Subjects/Keywords: data-driven modeling; statistical learning; density estimation; context learning; context-aware decision-making; pattern classification; multi-modal sensor fusion; sequential hypothesis testing; sequential learning; dynamic sensor selection; intelligent systems

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

APA (6th Edition):

Virani, N. (2017). Learning Data-driven Models for Decision-making in Intelligent Physical Systems. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/13813nnv105

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

Chicago Manual of Style (16th Edition):

Virani, Nurali. “Learning Data-driven Models for Decision-making in Intelligent Physical Systems.” 2017. Thesis, Penn State University. Accessed April 19, 2021. https://submit-etda.libraries.psu.edu/catalog/13813nnv105.

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

MLA Handbook (7th Edition):

Virani, Nurali. “Learning Data-driven Models for Decision-making in Intelligent Physical Systems.” 2017. Web. 19 Apr 2021.

Vancouver:

Virani N. Learning Data-driven Models for Decision-making in Intelligent Physical Systems. [Internet] [Thesis]. Penn State University; 2017. [cited 2021 Apr 19]. Available from: https://submit-etda.libraries.psu.edu/catalog/13813nnv105.

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

Council of Science Editors:

Virani N. Learning Data-driven Models for Decision-making in Intelligent Physical Systems. [Thesis]. Penn State University; 2017. Available from: https://submit-etda.libraries.psu.edu/catalog/13813nnv105

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


Penn State University

7. Proffitt, Richard P. Vision based map-to-image correspondence for attitude estimation in augmented reality applications.

Degree: 2016, Penn State University

 This dissertation proposes a methodology for attitude correction by matching two different representations of the same environment. This is accomplished by matching features extracted from… (more)

Subjects/Keywords: Augmented reality; horizon matching; sequence matching; vision-based attitude estimation; sensor fusion; visual navigation

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

APA (6th Edition):

Proffitt, R. P. (2016). Vision based map-to-image correspondence for attitude estimation in augmented reality applications. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/28856

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

Chicago Manual of Style (16th Edition):

Proffitt, Richard P. “Vision based map-to-image correspondence for attitude estimation in augmented reality applications.” 2016. Thesis, Penn State University. Accessed April 19, 2021. https://submit-etda.libraries.psu.edu/catalog/28856.

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

MLA Handbook (7th Edition):

Proffitt, Richard P. “Vision based map-to-image correspondence for attitude estimation in augmented reality applications.” 2016. Web. 19 Apr 2021.

Vancouver:

Proffitt RP. Vision based map-to-image correspondence for attitude estimation in augmented reality applications. [Internet] [Thesis]. Penn State University; 2016. [cited 2021 Apr 19]. Available from: https://submit-etda.libraries.psu.edu/catalog/28856.

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

Council of Science Editors:

Proffitt RP. Vision based map-to-image correspondence for attitude estimation in augmented reality applications. [Thesis]. Penn State University; 2016. Available from: https://submit-etda.libraries.psu.edu/catalog/28856

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


Penn State University

8. Dean, Adam. Terrain-Based Road Vehicle Localization Using Attitude Measurements .

Degree: 2008, Penn State University

 This research is focused on developing a road vehicle localization technique that is independent of Global Positioning System (GPS) by means of a terrain-based method… (more)

Subjects/Keywords: vehicle; terrain-based; estimation; kalman filter; particle filter; localization

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

APA (6th Edition):

Dean, A. (2008). Terrain-Based Road Vehicle Localization Using Attitude Measurements . (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/8997

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

Chicago Manual of Style (16th Edition):

Dean, Adam. “Terrain-Based Road Vehicle Localization Using Attitude Measurements .” 2008. Thesis, Penn State University. Accessed April 19, 2021. https://submit-etda.libraries.psu.edu/catalog/8997.

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

MLA Handbook (7th Edition):

Dean, Adam. “Terrain-Based Road Vehicle Localization Using Attitude Measurements .” 2008. Web. 19 Apr 2021.

Vancouver:

Dean A. Terrain-Based Road Vehicle Localization Using Attitude Measurements . [Internet] [Thesis]. Penn State University; 2008. [cited 2021 Apr 19]. Available from: https://submit-etda.libraries.psu.edu/catalog/8997.

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

Council of Science Editors:

Dean A. Terrain-Based Road Vehicle Localization Using Attitude Measurements . [Thesis]. Penn State University; 2008. Available from: https://submit-etda.libraries.psu.edu/catalog/8997

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

.