NDLI: Sensor-based distributed control for chain-typed self-reconfiguration

Content Provider	IEEE Xplore Digital Library
Author	Payne, K. Salemi, B. Will, P. Wei-Min Shen
Copyright Year	2004
Description	Author affiliation: Inf. Sci. Inst., Univ. of Southern California, Marina del Rey, CA, USA (Payne, K.; Salemi, B.; Will, P.; Wei-Min Shen)
Abstract	This paper describes two contributions for chain typed self-reconfigurable robots: a very illustrative self-reconfiguration task changing from "I" shape to "T" shape, and a sensor-based distributed control method for automatic planning and execution of self-reconfiguration. In the "I-to-T" task, a snake robot is to reconfigure itself into a tripod by docking the tail to a target module in the body, releasing a portion of the connected mass as a new leg, and switching to a new gait automatically. We first accomplished this task using predetermined instructions for individual modules without considering sensor inputs. We then developed a sensor-based approach using our hormone-inspired distributed control to allow the robot to dynamically accept the point of connection at run-time, align the tail and the target using sensors, and select appropriate actions based on modules' location in the configuration. Compared to the standard inverse kinematics, this new control approach is sensor-based and can endure the limited computational resources and uncertainties in the connections. It can be applied to self-reconfigurations that are not designed by the programmers but triggered by the environment.
Starting Page	2074
Ending Page	2080
File Size	555953
Page Count	7
File Format	PDF
ISBN	0780384636
DOI	10.1109/IROS.2004.1389703
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-09-28
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Distributed control Robot sensing systems Robotics and automation Shape control Legged locomotion Tail Leg Runtime Probability distribution Kinematics
Content Type	Text
Resource Type	Article

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