NDLI: Analytical and experimental results on multiagent cooperative behavior evolution

Content Provider	IEEE Xplore Digital Library
Author	Jiming Liu Jianbing Wu Xun Lai
Copyright Year	1999
Description	Author affiliation: Dept. of Comput. Sci., Hong Kong Baptist Univ., Kowloon, Hong Kong (Jiming Liu)
Abstract	The paper addresses the problem of automatically programming cooperative behaviors in a group of autonomous robots. The specific task that we consider here is for a group of distributed autonomous robots to cooperatively push an object toward a goal location. The difficulty of this task lies in that the task configurations of the robots with respect to the object do not follow any explicit, global control command, primarily due to certain modeling limitations as well as planning costs as in many real life applications. In such a case, it is important that the individual robots locally modify their motion strategies, and at the same time, create a desirable collective interaction between the distributed robot group and the object that can successfully bring the object to the goal location. In order to solve this problem, we have developed an evolutionary computation approach in which no centralized modeling and control is involved except a high level criterion for measuring the quality of robot task performance. The evolutionary approach to distributed robot behavioral programming is based on a fittest preserved genetic algorithm that takes into account the current positions and orientations of the robots relative to the object and the goal, and a weak global feedback on the collective task performing effect in relation to the goal if some new local motion strategies are employed by the robots.
Starting Page	1732
Ending Page	1739
File Size	738464
Page Count	8
File Format	PDF
ISBN	0780355369
DOI	10.1109/CEC.1999.785483
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-07-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robotics and automation Robot programming Automatic programming Motion planning Costs Evolutionary computation Centralized control Genetic programming Object oriented programming Genetic algorithms
Content Type	Text
Resource Type	Article

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