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Optimal arrest and guidance of a moving prismatic object using multiagents

Published online by Cambridge University Press:  01 January 2008

Pankaj Sharma ,
Anupam Saxena  and
Ashish Dutta
Pankaj Sharma
Affiliation:
Department of Mechanical Engineering, Indian Institute of Technology, Kanpur 208016INDIA.
Anupam Saxena
Affiliation:
Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY 14850, USA. E-mail: [email protected]
Ashish Dutta*
Affiliation:
Department of Mechanical Engineering, Nagoya University, Chikusa-ku, Furo-cho, Nagoya 464-8603, Japan.
*
*Corresponding author: E-mail: [email protected]
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Summary

Genetic algorithm is used to determine the optimal capture points for the multi agents required to grasp a moving generic prismatic object by arresting it in form closure. Thereafter, the agents approach their respective moving goals using a decentralized projective path planning algorithm. Post arrest, the object is guided along a desired linear path to a desired goal point. Form closure of the object is obtained using the concept of accessibility angle. A convex envelop is formed around the object, and the goal points on the object boundary are mapped onto the envelope. The robots approach the mapped goal points first, and then, converge on the actual object. This ensures that the agents reach the actual goal points almost simultaneously, and do not undergo looping at a local concave region. The object is assumed alive while being captured but is assumed compromised thereafter. Post arrest, robots alter their positions optimally around the object to transport it along a desired direction. Frictionless point contact between the object and a robot is assumed. The shape of the mobile robot is considered cylindrical such that it can only apply force along the outward radial direction. Simulation results are presented that illustrate the effectiveness of the proposed method.

Keywords

accessibility anglemulti agentsprojective path planninggenetic algorithm
Type
Article
Information
Robotica , Volume 26 , Issue 1 , January 2008 , pp. 41 - 53
Copyright
Copyright © Cambridge University Press 2007

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