Title: Learning complex tasks using a stepwise approach
Authors: Burdet, E
Nuttin, Marnix #
Issue Date: 30-Jan-1999
Publisher: Springer
Series Title: Journal of Intelligent & Robotic Systems vol:24 issue:1 pages:43-68
Abstract: This paper explores a stepwise learning approach based on a system¬ís decomposition into functional subsystems. Two case studies are examined: a visually guided robot that learns to track a maneuvering object, and a robot that learns to use the information from a force sensor in order to put a peg into a hole. These two applications show the features and advantages of the proposed approach: i) the subsystems naturally arise as functional components of the hardware and software; ii) these subsystems are building blocks of the robot behavior and can be combined in several ways for performing various tasks; iii) this decomposition makes it easier to check the performances and detect the cause of a malfunction; iv) only those subsystems for which a satisfactory solution is not available need to be learned; v) the strategy proposed for coordinating the optimization of all subsystems ensures an improvement at the task-level; vi) the overall system¬ís behavior is significantly improved by the stepwise learning approach.
ISSN: 0921-0296
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Production Engineering, Machine Design and Automation (PMA) Section
# (joint) last author

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