Visual programming by demonstration of grasping skills in the context of a mobile service robot using 1D-topology based self-organizing-maps

An approach to the task of Programming by demonstration (PbD) of grasping skills is introduced, where a mobile service robot is taught by a human instructor how to grasp a specific object. In contrast to other approaches the instructor demonstrates the grasping action several times to the robot to i...

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Veröffentlicht in:Robotics and autonomous systems Jg. 60; H. 3; S. 463 - 472
Hauptverfasser: Hüser, Markus, Zhang, Jianwei
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.03.2012
Schlagworte:
Algorithms
Approach trajectory
Grasp teaching
Grasping
Instructors
Programming
Repeated demonstrations
Robots
Self-organizing-map
Service robots
Skills
Tracking errors
Visual programming by demonstration
Approach trajectory
Grasp teaching
Repeated demonstrations
Self-organizing-map
Visual programming by demonstration
ISSN:0921-8890, 1872-793X
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Zusammenfassung:An approach to the task of Programming by demonstration (PbD) of grasping skills is introduced, where a mobile service robot is taught by a human instructor how to grasp a specific object. In contrast to other approaches the instructor demonstrates the grasping action several times to the robot to increase reconstruction performance. Only the robot’s stereoscopic vision system is used to track the instructor’s hand. The developed tracking algorithm is designed to not need artificial markers, data gloves or being restricted to fixed or difficult to calibrate sensor installations while at the same time being real-time capable on a mobile service robot with limited resources. Due to the instructor’s repeated demonstrations and his low repeating accuracy, every time a grasp is demonstrated the instructor performs it differently. To compensate for these variations and also to compensate for tracking errors, the use of a Self-Organizing-Map (SOM) with a one-dimensional topology is proposed. This SOM is used to generalize over differently demonstrated grasping actions and to reconstruct the intended approach trajectory of the instructor’s hand while grasping an object. The approach is implemented and evaluated on the service robot TASER using synthetically generated data as well as real world data. ► A real-time capable system for tracking the human hand is presented. ► Self-Organizing-Maps with a 1D-topology are proposed to learn grasping skills. ► The approach allows for repeated demonstrations of grasping skills. ► Repeated demonstrations improve the system’s reconstruction performance. ► Evaluation is done on synthetic and real world data on the service robot TASER.
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ISSN:0921-8890
1872-793X
DOI:10.1016/j.robot.2011.07.018