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You searched for +publisher:"Georgia Tech" +contributor:("Chernova, Sonia"). Showing records 1 – 10 of 10 total matches.

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Georgia Tech

1. Park, Daehyung. A multimodal execution monitor for assistive robots.

Degree: PhD, Interactive Computing, 2018, Georgia Tech

 Assistive robots have the potential to serve as caregivers, providing assistance with activities of daily living to people with disabilities. Monitoring when something has gone… (more)

Subjects/Keywords: Execution monitor; Assistive robot

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APA (6th Edition):

Park, D. (2018). A multimodal execution monitor for assistive robots. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59860

Chicago Manual of Style (16th Edition):

Park, Daehyung. “A multimodal execution monitor for assistive robots.” 2018. Doctoral Dissertation, Georgia Tech. Accessed March 28, 2020. http://hdl.handle.net/1853/59860.

MLA Handbook (7th Edition):

Park, Daehyung. “A multimodal execution monitor for assistive robots.” 2018. Web. 28 Mar 2020.

Vancouver:

Park D. A multimodal execution monitor for assistive robots. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/1853/59860.

Council of Science Editors:

Park D. A multimodal execution monitor for assistive robots. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59860


Georgia Tech

2. Krening, Samantha. Humans Teaching Intelligent Agents with Verbal Instruction.

Degree: PhD, Aerospace Engineering, 2019, Georgia Tech

 The widespread integration of robotics into everyday life requires significant improvement in the underlying machine learning (ML) agents to make them more accessible, customizable, and… (more)

Subjects/Keywords: Robotics; Machine Learning; Interactive Machine Learning; Human-Agent Interaction; Reinforcement Learning; Natural Language Processing; Human-Computer Interaction; Human Factors; Machine Learning Verification

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APA (6th Edition):

Krening, S. (2019). Humans Teaching Intelligent Agents with Verbal Instruction. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61232

Chicago Manual of Style (16th Edition):

Krening, Samantha. “Humans Teaching Intelligent Agents with Verbal Instruction.” 2019. Doctoral Dissertation, Georgia Tech. Accessed March 28, 2020. http://hdl.handle.net/1853/61232.

MLA Handbook (7th Edition):

Krening, Samantha. “Humans Teaching Intelligent Agents with Verbal Instruction.” 2019. Web. 28 Mar 2020.

Vancouver:

Krening S. Humans Teaching Intelligent Agents with Verbal Instruction. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/1853/61232.

Council of Science Editors:

Krening S. Humans Teaching Intelligent Agents with Verbal Instruction. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61232


Georgia Tech

3. Edwards, Ashley Deloris. Emulation and imitation via perceptual goal specifications.

Degree: PhD, Computer Science, 2019, Georgia Tech

 This dissertation aims to demonstrate how perceptual goal specifications may be used as alternative representations for specifying domain-specific reward functions for reinforcement learning. The works… (more)

Subjects/Keywords: Reinforcement learning; goal specification; imitation learning; reward design

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APA (6th Edition):

Edwards, A. D. (2019). Emulation and imitation via perceptual goal specifications. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61234

Chicago Manual of Style (16th Edition):

Edwards, Ashley Deloris. “Emulation and imitation via perceptual goal specifications.” 2019. Doctoral Dissertation, Georgia Tech. Accessed March 28, 2020. http://hdl.handle.net/1853/61234.

MLA Handbook (7th Edition):

Edwards, Ashley Deloris. “Emulation and imitation via perceptual goal specifications.” 2019. Web. 28 Mar 2020.

Vancouver:

Edwards AD. Emulation and imitation via perceptual goal specifications. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/1853/61234.

Council of Science Editors:

Edwards AD. Emulation and imitation via perceptual goal specifications. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61234


Georgia Tech

4. Okamoto, Kazuhide. Optimal Covariance Steering: Theory and Its Application to Autonomous Driving.

Degree: PhD, Aerospace Engineering, 2019, Georgia Tech

 Optimal control under uncertainty has been one of the central research topics in the control community for decades. While a number of theories have been… (more)

Subjects/Keywords: Stochastic Control; Optimal Control; Model Predictive Control; Vehicle Path Planning

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APA (6th Edition):

Okamoto, K. (2019). Optimal Covariance Steering: Theory and Its Application to Autonomous Driving. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62260

Chicago Manual of Style (16th Edition):

Okamoto, Kazuhide. “Optimal Covariance Steering: Theory and Its Application to Autonomous Driving.” 2019. Doctoral Dissertation, Georgia Tech. Accessed March 28, 2020. http://hdl.handle.net/1853/62260.

MLA Handbook (7th Edition):

Okamoto, Kazuhide. “Optimal Covariance Steering: Theory and Its Application to Autonomous Driving.” 2019. Web. 28 Mar 2020.

Vancouver:

Okamoto K. Optimal Covariance Steering: Theory and Its Application to Autonomous Driving. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/1853/62260.

Council of Science Editors:

Okamoto K. Optimal Covariance Steering: Theory and Its Application to Autonomous Driving. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62260


Georgia Tech

5. Bullard, Kalesha. Managing Learning Interactions for Collaborative Robot Learning.

Degree: PhD, Interactive Computing, 2019, Georgia Tech

 Robotic assistants should be able to actively engage their human partner(s) to generalize knowledge about relevant tasks within their shared environment. Yet a key challenge… (more)

Subjects/Keywords: interactive robot learning; active learning

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APA (6th Edition):

Bullard, K. (2019). Managing Learning Interactions for Collaborative Robot Learning. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62294

Chicago Manual of Style (16th Edition):

Bullard, Kalesha. “Managing Learning Interactions for Collaborative Robot Learning.” 2019. Doctoral Dissertation, Georgia Tech. Accessed March 28, 2020. http://hdl.handle.net/1853/62294.

MLA Handbook (7th Edition):

Bullard, Kalesha. “Managing Learning Interactions for Collaborative Robot Learning.” 2019. Web. 28 Mar 2020.

Vancouver:

Bullard K. Managing Learning Interactions for Collaborative Robot Learning. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/1853/62294.

Council of Science Editors:

Bullard K. Managing Learning Interactions for Collaborative Robot Learning. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62294


Georgia Tech

6. Chandrasekaran, Arjun. Towards Natural Human-AI Interactions in Vision and Language.

Degree: PhD, Interactive Computing, 2019, Georgia Tech

 Inter-human interaction is a rich form of communication. Human interactions typically leverage a good theory of mind, involve pragmatics, story-telling, humor, sarcasm, empathy, sympathy, etc.… (more)

Subjects/Keywords: AI; neural networks; Human-AI interaction; Human-AI collaboration; humor; narrative; storytelling; explainable AI; interpretability; predictability; guesswhich; human-in-loop evaluation

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APA (6th Edition):

Chandrasekaran, A. (2019). Towards Natural Human-AI Interactions in Vision and Language. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62323

Chicago Manual of Style (16th Edition):

Chandrasekaran, Arjun. “Towards Natural Human-AI Interactions in Vision and Language.” 2019. Doctoral Dissertation, Georgia Tech. Accessed March 28, 2020. http://hdl.handle.net/1853/62323.

MLA Handbook (7th Edition):

Chandrasekaran, Arjun. “Towards Natural Human-AI Interactions in Vision and Language.” 2019. Web. 28 Mar 2020.

Vancouver:

Chandrasekaran A. Towards Natural Human-AI Interactions in Vision and Language. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/1853/62323.

Council of Science Editors:

Chandrasekaran A. Towards Natural Human-AI Interactions in Vision and Language. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62323

7. Mukadam, Mustafa. Structured learning and inference for robot motion generation.

Degree: PhD, Electrical and Computer Engineering, 2019, Georgia Tech

 The ability to generate motions that accomplish desired tasks is fundamental to any robotic system. Robots must be able to generate such motions in a… (more)

Subjects/Keywords: Motion planning; Machine learning

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APA (6th Edition):

Mukadam, M. (2019). Structured learning and inference for robot motion generation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61714

Chicago Manual of Style (16th Edition):

Mukadam, Mustafa. “Structured learning and inference for robot motion generation.” 2019. Doctoral Dissertation, Georgia Tech. Accessed March 28, 2020. http://hdl.handle.net/1853/61714.

MLA Handbook (7th Edition):

Mukadam, Mustafa. “Structured learning and inference for robot motion generation.” 2019. Web. 28 Mar 2020.

Vancouver:

Mukadam M. Structured learning and inference for robot motion generation. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/1853/61714.

Council of Science Editors:

Mukadam M. Structured learning and inference for robot motion generation. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61714

8. Setter, Tina M. Psychologically consistent coordinated control of multi-agent teams.

Degree: PhD, Electrical and Computer Engineering, 2017, Georgia Tech

 The objective of this research is to describe both human-robot interactions and inter-robot interactions and analyze the behavior of the resulting multi-agent systems, while drawing… (more)

Subjects/Keywords: Multi-agent systems; Human-robot interaction; Coordinated control

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APA (6th Edition):

Setter, T. M. (2017). Psychologically consistent coordinated control of multi-agent teams. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58266

Chicago Manual of Style (16th Edition):

Setter, Tina M. “Psychologically consistent coordinated control of multi-agent teams.” 2017. Doctoral Dissertation, Georgia Tech. Accessed March 28, 2020. http://hdl.handle.net/1853/58266.

MLA Handbook (7th Edition):

Setter, Tina M. “Psychologically consistent coordinated control of multi-agent teams.” 2017. Web. 28 Mar 2020.

Vancouver:

Setter TM. Psychologically consistent coordinated control of multi-agent teams. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/1853/58266.

Council of Science Editors:

Setter TM. Psychologically consistent coordinated control of multi-agent teams. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/58266

9. Chu, Vivian. Teaching robots about human environments: Leveraging human interaction to efficiently learn and use multisensory object affordances.

Degree: PhD, Interactive Computing, 2018, Georgia Tech

 The real world is complex, unstructured, and contains high levels of uncertainty. Although past work shows that robots can successfully operate in situations where a… (more)

Subjects/Keywords: Robotics; Robot learning; Affordance learning; Human robot interaction; Multisensory data; Robot object manipulation; Human-guided robot exploration; Machine learning; Artificial intelligence; Haptics; Adaptable controllers; Multisensory robot control; Human-guided affordance learning; Interactive multisensory perception; Multimodal data; Sensor fusion

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APA (6th Edition):

Chu, V. (2018). Teaching robots about human environments: Leveraging human interaction to efficiently learn and use multisensory object affordances. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59839

Chicago Manual of Style (16th Edition):

Chu, Vivian. “Teaching robots about human environments: Leveraging human interaction to efficiently learn and use multisensory object affordances.” 2018. Doctoral Dissertation, Georgia Tech. Accessed March 28, 2020. http://hdl.handle.net/1853/59839.

MLA Handbook (7th Edition):

Chu, Vivian. “Teaching robots about human environments: Leveraging human interaction to efficiently learn and use multisensory object affordances.” 2018. Web. 28 Mar 2020.

Vancouver:

Chu V. Teaching robots about human environments: Leveraging human interaction to efficiently learn and use multisensory object affordances. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/1853/59839.

Council of Science Editors:

Chu V. Teaching robots about human environments: Leveraging human interaction to efficiently learn and use multisensory object affordances. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59839

10. Shim, Jaeeun. The benefits of other-oriented robot deception in human-robot interaction.

Degree: PhD, Electrical and Computer Engineering, 2017, Georgia Tech

 Deception is an essential social behavior for humans, and we can observe human deceptive behaviors in a variety of contexts including sports, culture, education, war,… (more)

Subjects/Keywords: Human-robot interaction; Robot deception; Robot ethics

…and how it should deceive others. Recent work at Georgia Tech explored the role of deception… 

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APA (6th Edition):

Shim, J. (2017). The benefits of other-oriented robot deception in human-robot interaction. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58253

Chicago Manual of Style (16th Edition):

Shim, Jaeeun. “The benefits of other-oriented robot deception in human-robot interaction.” 2017. Doctoral Dissertation, Georgia Tech. Accessed March 28, 2020. http://hdl.handle.net/1853/58253.

MLA Handbook (7th Edition):

Shim, Jaeeun. “The benefits of other-oriented robot deception in human-robot interaction.” 2017. Web. 28 Mar 2020.

Vancouver:

Shim J. The benefits of other-oriented robot deception in human-robot interaction. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2020 Mar 28]. Available from: http://hdl.handle.net/1853/58253.

Council of Science Editors:

Shim J. The benefits of other-oriented robot deception in human-robot interaction. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/58253

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