A visual-guided data collection system for learning from demonstration in mobile robotics

Li, J., Lilienthal, A. and Duckett, Tom (2010) A visual-guided data collection system for learning from demonstration in mobile robotics. In: ICINA 2010 - 2010 International Conference on Information, Networking and Automation, 17 - 19 October 2010, Kunming; China.

Full content URL: http://dx.doi.org/10.1109/ICINA.2010.5636387

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Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive


Robot learning from demonstration (LID) requires data collection for mapping the sensory states to motion action, which plays a significant role in the learning efficiency and effectiveness. This paper presents a visual-guided data collection system that allows a human demonstrator to teleoperate or to visually guide a mobile robot for the required behaviors, when simultaneously recording the sensory-motor training examples within LID. In the teleoperation mode, the human demonstrator can teleoperate the robot through a GUI that consists of the velocity control and sensory-motor recording commands with the monitoring windows for sonar, laser and visual image. In the visual-guided mode, the human demonstrator uses a green can as the command stick that is tracked by a pan-tilt-zoom (PTZ) camera. The system is implemented on a Peoplebot robot. Experiments show that both demonstration modes of the framework provide an user-friendly interface of data collection for the subsequent learning process of the robot. © 2010 IEEE.

Additional Information:Conference Code:82996
Keywords:Data collection, Data collection system, Guided modes, Learning efficiency, Learning from demonstration, Learning process, Mobile robotic, Pan-tilt-zoom camera, Sensory state, Tele-operations, Training example, User friendly interface, Visual image, Visual-guided demonstration, Data visualization, Demonstrations, Image recording, Laser windows, Remote control, Robot learning, Robots, Underwater acoustics, Data acquisition
Subjects:H Engineering > H670 Robotics and Cybernetics
Divisions:College of Science > School of Computer Science
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ID Code:10023
Deposited On:20 Dec 2013 09:51

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