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You searched for +publisher:"Georgia Tech" +contributor:("Thomaz, Andrea"). Showing records 1 – 30 of 35 total matches.

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Georgia Tech

1. 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 December 04, 2020. http://hdl.handle.net/1853/62294.

MLA Handbook (7th Edition):

Bullard, Kalesha. “Managing learning interactions for collaborative robot learning.” 2019. Web. 04 Dec 2020.

Vancouver:

Bullard K. Managing learning interactions for collaborative robot learning. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Dec 04]. 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

2. Subramanian, Kaushik. Policy-based exploration for efficient reinforcement learning.

Degree: PhD, Interactive Computing, 2020, Georgia Tech

 Reinforcement Learning (RL) is the field of research focused on solving sequential decision-making tasks modeled as Markov Decision Processes. Researchers have shown RL to be… (more)

Subjects/Keywords: Reinforcement learning; Exploration; Interactive learning; Active learning; Monte-carlo search; Bayesian

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APA (6th Edition):

Subramanian, K. (2020). Policy-based exploration for efficient reinforcement learning. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62831

Chicago Manual of Style (16th Edition):

Subramanian, Kaushik. “Policy-based exploration for efficient reinforcement learning.” 2020. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/62831.

MLA Handbook (7th Edition):

Subramanian, Kaushik. “Policy-based exploration for efficient reinforcement learning.” 2020. Web. 04 Dec 2020.

Vancouver:

Subramanian K. Policy-based exploration for efficient reinforcement learning. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/62831.

Council of Science Editors:

Subramanian K. Policy-based exploration for efficient reinforcement learning. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/62831


Georgia Tech

3. Grice, Phillip M. Assistive mobile manipulation for users with severe motor impairments.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2017, Georgia Tech

 Mobile robots that can physically manipulate their environments have the potential to help persons with motor impairments perform a variety of tasks, including self-care tasks.… (more)

Subjects/Keywords: Robotics; Manipulation; Assistive technology

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APA (6th Edition):

Grice, P. M. (2017). Assistive mobile manipulation for users with severe motor impairments. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60174

Chicago Manual of Style (16th Edition):

Grice, Phillip M. “Assistive mobile manipulation for users with severe motor impairments.” 2017. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/60174.

MLA Handbook (7th Edition):

Grice, Phillip M. “Assistive mobile manipulation for users with severe motor impairments.” 2017. Web. 04 Dec 2020.

Vancouver:

Grice PM. Assistive mobile manipulation for users with severe motor impairments. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/60174.

Council of Science Editors:

Grice PM. Assistive mobile manipulation for users with severe motor impairments. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/60174


Georgia Tech

4. Yu, Hong. A data-driven approach for personalized drama management.

Degree: PhD, Interactive Computing, 2015, Georgia Tech

 An interactive narrative is a form of digital entertainment in which players can create or influence a dramatic storyline through actions, typically by assuming the… (more)

Subjects/Keywords: Personalized drama manager; Interactive narrative; Player modeling; Prefix based collaborative filtering

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APA (6th Edition):

Yu, H. (2015). A data-driven approach for personalized drama management. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53851

Chicago Manual of Style (16th Edition):

Yu, Hong. “A data-driven approach for personalized drama management.” 2015. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/53851.

MLA Handbook (7th Edition):

Yu, Hong. “A data-driven approach for personalized drama management.” 2015. Web. 04 Dec 2020.

Vancouver:

Yu H. A data-driven approach for personalized drama management. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/53851.

Council of Science Editors:

Yu H. A data-driven approach for personalized drama management. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53851


Georgia Tech

5. Dantam, Neil Thomas. A linguistic method for robot verification programming and control.

Degree: PhD, Interactive Computing, 2014, Georgia Tech

 There are many competing techniques for specifying robot policies, each having advantages in different circumstances. To unify these techniques in a single framework, we use… (more)

Subjects/Keywords: Robotics; Formal language; Grammars; Policy representation

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APA (6th Edition):

Dantam, N. T. (2014). A linguistic method for robot verification programming and control. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54284

Chicago Manual of Style (16th Edition):

Dantam, Neil Thomas. “A linguistic method for robot verification programming and control.” 2014. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/54284.

MLA Handbook (7th Edition):

Dantam, Neil Thomas. “A linguistic method for robot verification programming and control.” 2014. Web. 04 Dec 2020.

Vancouver:

Dantam NT. A linguistic method for robot verification programming and control. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/54284.

Council of Science Editors:

Dantam NT. A linguistic method for robot verification programming and control. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/54284


Georgia Tech

6. Cosgun, Akansel. Navigation behavior design and representations for a people aware mobile robot system.

Degree: PhD, Interactive Computing, 2016, Georgia Tech

 There are millions of robots in operation around the world today, and almost all of them operate on factory floors in isolation from people. However,… (more)

Subjects/Keywords: Robotics; Navigation; Mobile robots; Path planning

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APA (6th Edition):

Cosgun, A. (2016). Navigation behavior design and representations for a people aware mobile robot system. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54944

Chicago Manual of Style (16th Edition):

Cosgun, Akansel. “Navigation behavior design and representations for a people aware mobile robot system.” 2016. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/54944.

MLA Handbook (7th Edition):

Cosgun, Akansel. “Navigation behavior design and representations for a people aware mobile robot system.” 2016. Web. 04 Dec 2020.

Vancouver:

Cosgun A. Navigation behavior design and representations for a people aware mobile robot system. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/54944.

Council of Science Editors:

Cosgun A. Navigation behavior design and representations for a people aware mobile robot system. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/54944


Georgia Tech

7. Huaman, Ana Consuelo. Grasp selection strategies for robot manipulation using a superquadric-based object representation.

Degree: PhD, Computer Science, 2016, Georgia Tech

 This thesis presents work on the implementation of a robotic system targeted to perform a set of basic manipulation tasks instructed by a human user.… (more)

Subjects/Keywords: Grasping; Robot manipulation

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APA (6th Edition):

Huaman, A. C. (2016). Grasp selection strategies for robot manipulation using a superquadric-based object representation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55672

Chicago Manual of Style (16th Edition):

Huaman, Ana Consuelo. “Grasp selection strategies for robot manipulation using a superquadric-based object representation.” 2016. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/55672.

MLA Handbook (7th Edition):

Huaman, Ana Consuelo. “Grasp selection strategies for robot manipulation using a superquadric-based object representation.” 2016. Web. 04 Dec 2020.

Vancouver:

Huaman AC. Grasp selection strategies for robot manipulation using a superquadric-based object representation. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/55672.

Council of Science Editors:

Huaman AC. Grasp selection strategies for robot manipulation using a superquadric-based object representation. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55672


Georgia Tech

8. Bai, Yunfei. Simulating Human Motion for Object Manipulation.

Degree: PhD, Computer Science, 2015, Georgia Tech

 Performing object manipulation with full-body and dexterous hands is an essential human activity in everyday environment. Although problems involving object manipulation have been frequently studied… (more)

Subjects/Keywords: Computer graphics; Computer animation; Character animation; Physics based simulation

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APA (6th Edition):

Bai, Y. (2015). Simulating Human Motion for Object Manipulation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56187

Chicago Manual of Style (16th Edition):

Bai, Yunfei. “Simulating Human Motion for Object Manipulation.” 2015. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/56187.

MLA Handbook (7th Edition):

Bai, Yunfei. “Simulating Human Motion for Object Manipulation.” 2015. Web. 04 Dec 2020.

Vancouver:

Bai Y. Simulating Human Motion for Object Manipulation. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/56187.

Council of Science Editors:

Bai Y. Simulating Human Motion for Object Manipulation. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/56187


Georgia Tech

9. A, Yongga. Dynamic humanoid locomotion: Hybrid zero dynamics based gait optimization via direct collocation methods.

Degree: PhD, Mechanical Engineering, 2016, Georgia Tech

 Hybrid zero dynamics (HZD) has emerged as a popular framework for dynamic and underactuated bipedal walking, but has significant implementation difficulties when applied to the… (more)

Subjects/Keywords: Humanoid locomotion; Nonlinear optimization; Hybrid zero dynamics; Direct collocation; Pseudospectral optimization

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APA (6th Edition):

A, Y. (2016). Dynamic humanoid locomotion: Hybrid zero dynamics based gait optimization via direct collocation methods. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56249

Chicago Manual of Style (16th Edition):

A, Yongga. “Dynamic humanoid locomotion: Hybrid zero dynamics based gait optimization via direct collocation methods.” 2016. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/56249.

MLA Handbook (7th Edition):

A, Yongga. “Dynamic humanoid locomotion: Hybrid zero dynamics based gait optimization via direct collocation methods.” 2016. Web. 04 Dec 2020.

Vancouver:

A Y. Dynamic humanoid locomotion: Hybrid zero dynamics based gait optimization via direct collocation methods. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/56249.

Council of Science Editors:

A Y. Dynamic humanoid locomotion: Hybrid zero dynamics based gait optimization via direct collocation methods. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/56249


Georgia Tech

10. Fitzgerald, Tesca Kate. Human-guided task transfer for interactive robots.

Degree: PhD, Interactive Computing, 2020, Georgia Tech

 Adaptability is an essential skill in human cognition, enabling us to draw from our extensive, life-long experiences with various objects and tasks in order to… (more)

Subjects/Keywords: Artificial intelligence; Cognitive robotics; Human-robot interaction; Transfer learning

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APA (6th Edition):

Fitzgerald, T. K. (2020). Human-guided task transfer for interactive robots. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/63630

Chicago Manual of Style (16th Edition):

Fitzgerald, Tesca Kate. “Human-guided task transfer for interactive robots.” 2020. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/63630.

MLA Handbook (7th Edition):

Fitzgerald, Tesca Kate. “Human-guided task transfer for interactive robots.” 2020. Web. 04 Dec 2020.

Vancouver:

Fitzgerald TK. Human-guided task transfer for interactive robots. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/63630.

Council of Science Editors:

Fitzgerald TK. Human-guided task transfer for interactive robots. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/63630


Georgia Tech

11. Park, Hae Won. Robot learners: interactive instance-based learning with social robots.

Degree: PhD, Electrical and Computer Engineering, 2014, Georgia Tech

 On one hand, academic and industrial researchers have been developing and deploying robots that are used as educational tutors, mediators, and motivational tools. On the… (more)

Subjects/Keywords: Robotics; Socially assistive robotics; Case-based reasoning; Interactive machine learning; Touchscreen mobile device

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APA (6th Edition):

Park, H. W. (2014). Robot learners: interactive instance-based learning with social robots. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53442

Chicago Manual of Style (16th Edition):

Park, Hae Won. “Robot learners: interactive instance-based learning with social robots.” 2014. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/53442.

MLA Handbook (7th Edition):

Park, Hae Won. “Robot learners: interactive instance-based learning with social robots.” 2014. Web. 04 Dec 2020.

Vancouver:

Park HW. Robot learners: interactive instance-based learning with social robots. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/53442.

Council of Science Editors:

Park HW. Robot learners: interactive instance-based learning with social robots. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/53442

12. Scholz, Jonathan. Physics-based reinforcement learning for autonomous manipulation.

Degree: PhD, Interactive Computing, 2015, Georgia Tech

 With recent research advances, the dream of bringing domestic robots into our everyday lives has become more plausible than ever. Domestic robotics has grown dramatically… (more)

Subjects/Keywords: Machine learning; Robotics; Reinforcement learning

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APA (6th Edition):

Scholz, J. (2015). Physics-based reinforcement learning for autonomous manipulation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54366

Chicago Manual of Style (16th Edition):

Scholz, Jonathan. “Physics-based reinforcement learning for autonomous manipulation.” 2015. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/54366.

MLA Handbook (7th Edition):

Scholz, Jonathan. “Physics-based reinforcement learning for autonomous manipulation.” 2015. Web. 04 Dec 2020.

Vancouver:

Scholz J. Physics-based reinforcement learning for autonomous manipulation. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/54366.

Council of Science Editors:

Scholz J. Physics-based reinforcement learning for autonomous manipulation. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54366

13. Brown, LaVonda N. Developing an engagement and social interaction model for a robotic educational agent.

Degree: PhD, Electrical and Computer Engineering, 2015, Georgia Tech

 Effective educational agents should accomplish four essential goals during a student's learning process: 1) monitor engagement, 2) re-engage when appropriate, 3) teach novel tasks, and… (more)

Subjects/Keywords: Educational technology; Social robotics

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APA (6th Edition):

Brown, L. N. (2015). Developing an engagement and social interaction model for a robotic educational agent. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54440

Chicago Manual of Style (16th Edition):

Brown, LaVonda N. “Developing an engagement and social interaction model for a robotic educational agent.” 2015. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/54440.

MLA Handbook (7th Edition):

Brown, LaVonda N. “Developing an engagement and social interaction model for a robotic educational agent.” 2015. Web. 04 Dec 2020.

Vancouver:

Brown LN. Developing an engagement and social interaction model for a robotic educational agent. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/54440.

Council of Science Editors:

Brown LN. Developing an engagement and social interaction model for a robotic educational agent. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54440

14. LaViers, Amy. Choreographic abstractions for style-based robotic motion.

Degree: PhD, Electrical and Computer Engineering, 2013, Georgia Tech

 What does it mean to do the disco? Or perform a cheerleading routine? Or move in a style appropriate for a given mode of human… (more)

Subjects/Keywords: Optimal control; Supervisory control; Robotics; Dance; Motion; Robots Motion; Human mechanics; Robotics Human factors

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APA (6th Edition):

LaViers, A. (2013). Choreographic abstractions for style-based robotic motion. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/49033

Chicago Manual of Style (16th Edition):

LaViers, Amy. “Choreographic abstractions for style-based robotic motion.” 2013. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/49033.

MLA Handbook (7th Edition):

LaViers, Amy. “Choreographic abstractions for style-based robotic motion.” 2013. Web. 04 Dec 2020.

Vancouver:

LaViers A. Choreographic abstractions for style-based robotic motion. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/49033.

Council of Science Editors:

LaViers A. Choreographic abstractions for style-based robotic motion. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/49033

15. Gallagher, William John. Modeling of operator action for intelligent control of haptic human-robot interfaces.

Degree: PhD, Aerospace Engineering, 2013, Georgia Tech

 Control of systems requiring direct physical human-robot interaction (pHRI) requires special consideration of the motion, dynamics, and control of both the human and the robot.… (more)

Subjects/Keywords: Human-robot interaction; Haptics; Force assist; Exoskeleton; Muscle control; Human engineering; Haptic devices; Touch; Robotics; Robotics Human factors; Robots Control systems

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APA (6th Edition):

Gallagher, W. J. (2013). Modeling of operator action for intelligent control of haptic human-robot interfaces. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/50258

Chicago Manual of Style (16th Edition):

Gallagher, William John. “Modeling of operator action for intelligent control of haptic human-robot interfaces.” 2013. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/50258.

MLA Handbook (7th Edition):

Gallagher, William John. “Modeling of operator action for intelligent control of haptic human-robot interfaces.” 2013. Web. 04 Dec 2020.

Vancouver:

Gallagher WJ. Modeling of operator action for intelligent control of haptic human-robot interfaces. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/50258.

Council of Science Editors:

Gallagher WJ. Modeling of operator action for intelligent control of haptic human-robot interfaces. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/50258

16. Simpkins, Christopher Lee. Integrating reinforcement learning into a programming language.

Degree: PhD, Computer Science, 2017, Georgia Tech

 Reinforcement learning is a promising solution to the intelligent agent problem, namely, given the state of the world, which action should an agent take to… (more)

Subjects/Keywords: Machine learning; Reinforcement learning; Modular reinforcement learning; Programming languages; Domain specific languages; Software engineering; Artificial intelligence; Intelligent agents

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APA (6th Edition):

Simpkins, C. L. (2017). Integrating reinforcement learning into a programming language. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58683

Chicago Manual of Style (16th Edition):

Simpkins, Christopher Lee. “Integrating reinforcement learning into a programming language.” 2017. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/58683.

MLA Handbook (7th Edition):

Simpkins, Christopher Lee. “Integrating reinforcement learning into a programming language.” 2017. Web. 04 Dec 2020.

Vancouver:

Simpkins CL. Integrating reinforcement learning into a programming language. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/58683.

Council of Science Editors:

Simpkins CL. Integrating reinforcement learning into a programming language. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/58683

17. Cobo Rus, Luis Carlos. Leveraging attention focus for effective reinforcement learning in complex domains.

Degree: PhD, Electrical and Computer Engineering, 2013, Georgia Tech

 One of the hardest challenges in the field of machine learning is to build agents, such as robotic assistants in homes and hospitals, that can… (more)

Subjects/Keywords: Reinforcement learning; Learning from demonstration; Dimensionality reduction; Machine learning; Stochastic processes; Autonomous robots; Robots; Intelligent agents (Computer software)

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APA (6th Edition):

Cobo Rus, L. C. (2013). Leveraging attention focus for effective reinforcement learning in complex domains. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/47618

Chicago Manual of Style (16th Edition):

Cobo Rus, Luis Carlos. “Leveraging attention focus for effective reinforcement learning in complex domains.” 2013. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/47618.

MLA Handbook (7th Edition):

Cobo Rus, Luis Carlos. “Leveraging attention focus for effective reinforcement learning in complex domains.” 2013. Web. 04 Dec 2020.

Vancouver:

Cobo Rus LC. Leveraging attention focus for effective reinforcement learning in complex domains. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/47618.

Council of Science Editors:

Cobo Rus LC. Leveraging attention focus for effective reinforcement learning in complex domains. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/47618

18. Kunz, Tobias. Time-optimal sampling-based motion planning for manipulators with acceleration limits.

Degree: PhD, Interactive Computing, 2015, Georgia Tech

 Robot actuators have physical limitations in how fast they can change their velocity. The more accurately planning algorithms consider these limitations, the better the robot… (more)

Subjects/Keywords: Robotics; Motion planning; Kinodynamic planning; Sampling-based planning

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APA (6th Edition):

Kunz, T. (2015). Time-optimal sampling-based motion planning for manipulators with acceleration limits. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53569

Chicago Manual of Style (16th Edition):

Kunz, Tobias. “Time-optimal sampling-based motion planning for manipulators with acceleration limits.” 2015. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/53569.

MLA Handbook (7th Edition):

Kunz, Tobias. “Time-optimal sampling-based motion planning for manipulators with acceleration limits.” 2015. Web. 04 Dec 2020.

Vancouver:

Kunz T. Time-optimal sampling-based motion planning for manipulators with acceleration limits. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/53569.

Council of Science Editors:

Kunz T. Time-optimal sampling-based motion planning for manipulators with acceleration limits. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53569

19. Huckaby, Jacob O. Knowledge transfer in robot manipulation tasks.

Degree: PhD, Electrical and Computer Engineering, 2014, Georgia Tech

 Technology today has progressed to the point that the true potential of robotics is beginning to be realized. However, programming robots to be robust across… (more)

Subjects/Keywords: Robotics; Manufacturing robotics; Robots Control systems; Robots, Industrial; Automatic machinery; Manipulators (Mechanism)

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APA (6th Edition):

Huckaby, J. O. (2014). Knowledge transfer in robot manipulation tasks. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/51902

Chicago Manual of Style (16th Edition):

Huckaby, Jacob O. “Knowledge transfer in robot manipulation tasks.” 2014. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/51902.

MLA Handbook (7th Edition):

Huckaby, Jacob O. “Knowledge transfer in robot manipulation tasks.” 2014. Web. 04 Dec 2020.

Vancouver:

Huckaby JO. Knowledge transfer in robot manipulation tasks. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/51902.

Council of Science Editors:

Huckaby JO. Knowledge transfer in robot manipulation tasks. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/51902

20. Gielniak, Michael Joseph. Adaptation of task-aware, communicative variance for motion control in social humanoid robotic applications.

Degree: PhD, Electrical and Computer Engineering, 2012, Georgia Tech

 An algorithm for generating communicative, human-like motion for social humanoid robots was developed. Anticipation, exaggeration, and secondary motion were demonstrated as examples of communication. Spatiotemporal… (more)

Subjects/Keywords: Motor coordination; DOF coupling; Kolmogorov-Sinai entropy; Animation principles; Androids; Robots; Robots Programming; Human-robot interaction; Robots Motion; Algorithms

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APA (6th Edition):

Gielniak, M. J. (2012). Adaptation of task-aware, communicative variance for motion control in social humanoid robotic applications. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/43591

Chicago Manual of Style (16th Edition):

Gielniak, Michael Joseph. “Adaptation of task-aware, communicative variance for motion control in social humanoid robotic applications.” 2012. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/43591.

MLA Handbook (7th Edition):

Gielniak, Michael Joseph. “Adaptation of task-aware, communicative variance for motion control in social humanoid robotic applications.” 2012. Web. 04 Dec 2020.

Vancouver:

Gielniak MJ. Adaptation of task-aware, communicative variance for motion control in social humanoid robotic applications. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/43591.

Council of Science Editors:

Gielniak MJ. Adaptation of task-aware, communicative variance for motion control in social humanoid robotic applications. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/43591

21. Irani, Arya John. Utilizing negative policy information to accelerate reinforcement learning.

Degree: PhD, Interactive Computing, 2015, Georgia Tech

 A pilot study by Subramanian et al. on Markov decision problem task decomposition by humans revealed that participants break down tasks into both short-term subgoals… (more)

Subjects/Keywords:

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APA (6th Edition):

Irani, A. J. (2015). Utilizing negative policy information to accelerate reinforcement learning. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53481

Chicago Manual of Style (16th Edition):

Irani, Arya John. “Utilizing negative policy information to accelerate reinforcement learning.” 2015. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/53481.

MLA Handbook (7th Edition):

Irani, Arya John. “Utilizing negative policy information to accelerate reinforcement learning.” 2015. Web. 04 Dec 2020.

Vancouver:

Irani AJ. Utilizing negative policy information to accelerate reinforcement learning. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/53481.

Council of Science Editors:

Irani AJ. Utilizing negative policy information to accelerate reinforcement learning. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53481

22. De la Croix, Jean-Pierre. Characterizing and facilitating human interactions with swarms of mobile robots.

Degree: PhD, Electrical and Computer Engineering, 2015, Georgia Tech

 Since humans and robots often share workspaces and interact with each other to complete tasks cooperatively, as is the case, for example, in automated warehouses… (more)

Subjects/Keywords: Control theory; Robotics; Human-swarm interactions

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APA (6th Edition):

De la Croix, J. (2015). Characterizing and facilitating human interactions with swarms of mobile robots. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53524

Chicago Manual of Style (16th Edition):

De la Croix, Jean-Pierre. “Characterizing and facilitating human interactions with swarms of mobile robots.” 2015. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/53524.

MLA Handbook (7th Edition):

De la Croix, Jean-Pierre. “Characterizing and facilitating human interactions with swarms of mobile robots.” 2015. Web. 04 Dec 2020.

Vancouver:

De la Croix J. Characterizing and facilitating human interactions with swarms of mobile robots. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/53524.

Council of Science Editors:

De la Croix J. Characterizing and facilitating human interactions with swarms of mobile robots. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53524

23. Robinette, Paul. Developing robots that impact human-robot trust in emergency evacuations.

Degree: PhD, Electrical and Computer Engineering, 2015, Georgia Tech

 High-risk, time-critical situations require trust for humans to interact with other agents even if they have never interacted with the agents before. In the near… (more)

Subjects/Keywords: Robotics; Human-robot interaction; Human-robot trust; Rescue robots

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APA (6th Edition):

Robinette, P. (2015). Developing robots that impact human-robot trust in emergency evacuations. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54415

Chicago Manual of Style (16th Edition):

Robinette, Paul. “Developing robots that impact human-robot trust in emergency evacuations.” 2015. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/54415.

MLA Handbook (7th Edition):

Robinette, Paul. “Developing robots that impact human-robot trust in emergency evacuations.” 2015. Web. 04 Dec 2020.

Vancouver:

Robinette P. Developing robots that impact human-robot trust in emergency evacuations. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/54415.

Council of Science Editors:

Robinette P. Developing robots that impact human-robot trust in emergency evacuations. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54415

24. Akgun, Baris. Robots learning actions and goals from everyday people.

Degree: PhD, Interactive Computing, 2015, Georgia Tech

 Robots are destined to move beyond the caged factory floors towards domains where they will be interacting closely with humans. They will encounter highly varied… (more)

Subjects/Keywords: Robotics; Self-learning; Social-learning; Learning from demonstration; Human robot interaction

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APA (6th Edition):

Akgun, B. (2015). Robots learning actions and goals from everyday people. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54435

Chicago Manual of Style (16th Edition):

Akgun, Baris. “Robots learning actions and goals from everyday people.” 2015. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/54435.

MLA Handbook (7th Edition):

Akgun, Baris. “Robots learning actions and goals from everyday people.” 2015. Web. 04 Dec 2020.

Vancouver:

Akgun B. Robots learning actions and goals from everyday people. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/54435.

Council of Science Editors:

Akgun B. Robots learning actions and goals from everyday people. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54435

25. Chao, Crystal. Timing multimodal turn-taking in human-robot cooperative activity.

Degree: PhD, Computer Science, 2015, Georgia Tech

 Turn-taking is a fundamental process that governs social interaction. When humans interact, they naturally take initiative and relinquish control to each other using verbal and… (more)

Subjects/Keywords: Turn-taking; Situated dialogue; Collaborative discourse; Collaborative manipulation; Multimodal interaction; Situated dialogue; Collaborative discourse; Collaborative manipulation; Multimodal interaction; Social interaction; Situated dialogue; Collaborative discourse; Collaborative manipulation; Multimodal interaction; Social interaction; Human-robot collaboration; Human-robot interaction; Embodied conversational agents; Behavior architectures; Timed Petri nets; Artificial intelligence; Autonomous systems

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APA (6th Edition):

Chao, C. (2015). Timing multimodal turn-taking in human-robot cooperative activity. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54904

Chicago Manual of Style (16th Edition):

Chao, Crystal. “Timing multimodal turn-taking in human-robot cooperative activity.” 2015. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/54904.

MLA Handbook (7th Edition):

Chao, Crystal. “Timing multimodal turn-taking in human-robot cooperative activity.” 2015. Web. 04 Dec 2020.

Vancouver:

Chao C. Timing multimodal turn-taking in human-robot cooperative activity. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/54904.

Council of Science Editors:

Chao C. Timing multimodal turn-taking in human-robot cooperative activity. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54904

26. Forsthoefel, Dana. Leap segmentation in mobile image and video analysis.

Degree: PhD, Electrical and Computer Engineering, 2013, Georgia Tech

 As demand for real-time image processing increases, the need to improve the efficiency of image processing systems is growing. The process of image segmentation is… (more)

Subjects/Keywords: Computer vision; Image segmentation; Real-time and embedded systems; Image segmentation; Computer vision

Georgia Tech for use in vision evaluation experiments. The sequences contain fast-moving traffic… …Georgia Tech is developed and presented for use in vision evaluation experiments (… 

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APA (6th Edition):

Forsthoefel, D. (2013). Leap segmentation in mobile image and video analysis. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/50285

Chicago Manual of Style (16th Edition):

Forsthoefel, Dana. “Leap segmentation in mobile image and video analysis.” 2013. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/50285.

MLA Handbook (7th Edition):

Forsthoefel, Dana. “Leap segmentation in mobile image and video analysis.” 2013. Web. 04 Dec 2020.

Vancouver:

Forsthoefel D. Leap segmentation in mobile image and video analysis. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/50285.

Council of Science Editors:

Forsthoefel D. Leap segmentation in mobile image and video analysis. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/50285

27. McGreggor, Brian Keith. Fractal reasoning.

Degree: PhD, Interactive Computing, 2013, Georgia Tech

 Humans are experts at understanding what they see. Similarity and analogy play a significant role in making sense of the visual world by forming analogies… (more)

Subjects/Keywords: Analogy; Artificial intelligence; Knowledge representation; Fractals; Reasoning; Visual analogy; Reasoning; Artificial intelligence; Similarity (Psychology); Fractal analysis

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APA (6th Edition):

McGreggor, B. K. (2013). Fractal reasoning. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/50337

Chicago Manual of Style (16th Edition):

McGreggor, Brian Keith. “Fractal reasoning.” 2013. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/50337.

MLA Handbook (7th Edition):

McGreggor, Brian Keith. “Fractal reasoning.” 2013. Web. 04 Dec 2020.

Vancouver:

McGreggor BK. Fractal reasoning. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/50337.

Council of Science Editors:

McGreggor BK. Fractal reasoning. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/50337

28. Nguyen, Hai Dai. Constructing mobile manipulation behaviors using expert interfaces and autonomous robot learning.

Degree: PhD, Computer Science, 2013, Georgia Tech

 With current state-of-the-art approaches, development of a single mobile manipulation capability can be a labor-intensive process that presents an impediment to the creation of general… (more)

Subjects/Keywords: Robot authoring interfaces; Autonomous learning; Robot learning; Mobile manipulation; Home robotics; Robots; Machine learning; End-user computing; Robots Control systems

…22 6 The Georgia Tech Aware Home… …this work. Additionally, our work was performed in the Georgia Tech Aware Home, the… 

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APA (6th Edition):

Nguyen, H. D. (2013). Constructing mobile manipulation behaviors using expert interfaces and autonomous robot learning. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/50206

Chicago Manual of Style (16th Edition):

Nguyen, Hai Dai. “Constructing mobile manipulation behaviors using expert interfaces and autonomous robot learning.” 2013. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/50206.

MLA Handbook (7th Edition):

Nguyen, Hai Dai. “Constructing mobile manipulation behaviors using expert interfaces and autonomous robot learning.” 2013. Web. 04 Dec 2020.

Vancouver:

Nguyen HD. Constructing mobile manipulation behaviors using expert interfaces and autonomous robot learning. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/50206.

Council of Science Editors:

Nguyen HD. Constructing mobile manipulation behaviors using expert interfaces and autonomous robot learning. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/50206

29. 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 December 04, 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. 04 Dec 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 Dec 04]. 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

30. Sung, Ja-Young. Towards the human-centered design of everyday robots.

Degree: PhD, Computing, 2011, Georgia Tech

 The recent advancement of robotic technology brings robots closer to assisting us in our everyday spaces, providing support for healthcare, cleaning, entertaining and other tasks.… (more)

Subjects/Keywords: Qualitative study; Domestic robots; Robot design guidelines; Human-robot interaction; Robotics; Robots; Personal robotics

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APA (6th Edition):

Sung, J. (2011). Towards the human-centered design of everyday robots. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/39539

Chicago Manual of Style (16th Edition):

Sung, Ja-Young. “Towards the human-centered design of everyday robots.” 2011. Doctoral Dissertation, Georgia Tech. Accessed December 04, 2020. http://hdl.handle.net/1853/39539.

MLA Handbook (7th Edition):

Sung, Ja-Young. “Towards the human-centered design of everyday robots.” 2011. Web. 04 Dec 2020.

Vancouver:

Sung J. Towards the human-centered design of everyday robots. [Internet] [Doctoral dissertation]. Georgia Tech; 2011. [cited 2020 Dec 04]. Available from: http://hdl.handle.net/1853/39539.

Council of Science Editors:

Sung J. Towards the human-centered design of everyday robots. [Doctoral Dissertation]. Georgia Tech; 2011. Available from: http://hdl.handle.net/1853/39539

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