NDLI: Adaptive behavior acquisition of collision avoidance among multiple autonomous mobile robots

Content Provider	IEEE Xplore Digital Library
Author	Arai, Y. Fujii, T. Asama, H. Kataoka, Y. Kaetsu, H. Matsumoto, A. Endo, I.
Copyright Year	1997
Description	Author affiliation: Graduate Sch. of Sci. & Eng., Saitama Univ., Urawa, Japan (Arai, Y.)
Abstract	We discuss adaptive behavior acquisition for collision avoidance among multiple autonomous mobile robots which are equipped with the locally communicable infrared sensory system (LOCISS). The LOCISS is a local sensing device for collision avoidance by which robots can detect other robots and obstacles and discriminate them by exchanging relevant information. We (1996) reported previously a collision avoidance method between two robots based on the predetermined rules using LOCISS. It is, however, difficult to realize collision avoidance among three or more robots by the predetermined rules only because situations around the robots become more complicated as the number of robots increases. Thus, it is desirable for the robots to have an adaptive capability for acquisition of the behaviors to avoid collision with other robots and obstacles. To acquire the adaptive behavior, the reinforcement learning is introduced in this paper. It is shown that appropriate behaviors for collision avoidance can be successfully acquired through the proposed learning process.
Starting Page	1762
Ending Page	1767
File Size	559280
Page Count	6
File Format	PDF
ISBN	0780341198
DOI	10.1109/IROS.1997.656599
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-09-11
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Collision avoidance Mobile robots Robot sensing systems Infrared sensors Educational institutions Chemical sensors Chemical engineering Mechanical engineering Path planning Neural networks
Content Type	Text
Resource Type	Article

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