A data collection framework for learning from demonstration in mobile robotics

Li, J. and Wang, B. and Duckett, Tom (2010) A data collection framework for learning from demonstration in mobile robotics. In: IASTED International Conference on Robotics and Applications, RA 2010, 1 - 3 November 2010, Cambridge, MA; United States.

Full content URL: http://dx.doi.org/10.2316/P.2010.706-034

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

Abstract

Robot learning from demonstration (LfD) requires data collection for mapping the sensory states to motion action, which plays a significant role in the learning efficiency and effectiveness. In this paper we present a data collection framework that allows a human demonstrator to teleoperate or to visually guide a mobile robot for the required behaviors, while the sensory-motor examples are simultaneously gathered. 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 framework 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.

Additional Information:Conference Code:89095
Keywords:Data collection, Learning efficiency, Learning from demonstration, Learning process, Mobile robotic, Pan-tilt-zoom camera, Sensory state, Tele-operations, User friendly interface, Visual image, Image recording, Laser windows, Remote control, Robot learning, Robotics, Robots, Underwater acoustics, Data acquisition, bmjdoi
Subjects:H Engineering > H670 Robotics and Cybernetics
Divisions:College of Science > School of Computer Science
ID Code:10050
Deposited On:22 Jan 2014 10:37

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