Title :
Behavior recognition for Learning from Demonstration
Author :
Billing, Erik A. ; Hellström, Thomas ; Janlert, Lars-Erik
Author_Institution :
Dept. of Comput. Sci., Umea Univ., Umea, Sweden
Abstract :
Two methods for behavior recognition are presented and evaluated. Both methods are based on the dynamic temporal difference algorithm Predictive Sequence Learning (PSL) which has previously been proposed as a learning algorithm for robot control. One strength of the proposed recognition methods is that the model PSL builds to recognize behaviors is identical to that used for control, implying that the controller (inverse model) and the recognition algorithm (forward model) can be implemented as two aspects of the same model. The two proposed methods, PSLE-Comparison and PSLH-Comparison, are evaluated in a Learning from Demonstration setting, where each algorithm should recognize a known skill in a demonstration performed via teleoperation. PSLH-Comparison produced the smallest recognition error. The results indicate that PSLH-Comparison could be a suitable algorithm for integration in a hierarchical control system consistent with recent models of human perception and motor control.
Keywords :
learning (artificial intelligence); pattern recognition; telerobotics; PSLE-Comparison method; PSLH-Comparison method; behavior recognition; hierarchical control system; human perception model; learning algorithm; learning-from-demonstration setting; motor control model; predictive sequence learning; robot control; teleoperation; Context modeling; Explosions; Heuristic algorithms; Humans; Inverse problems; Prediction algorithms; Predictive models; Robot control; Robot kinematics; Robot sensing systems; Autonomous Agents; Learning and Adaptive Systems; Neurorobotics;
Conference_Titel :
Robotics and Automation (ICRA), 2010 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4244-5038-1
Electronic_ISBN :
1050-4729
DOI :
10.1109/ROBOT.2010.5509912