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Immune–wavelet optimization for path planning of large-scale robots

Published online by Cambridge University Press:  19 July 2013

Saeid Asadi ,
Vahid Azimirad ,
Ali Eslami  and
Saeid Karimian Eghbal
Saeid Asadi
Affiliation:
Biomechatronics Laboratory, School of Engineering Emerging Technologies, University of Tabriz, Tabriz, Iran
Vahid Azimirad*
Affiliation:
Biomechatronics Laboratory, School of Engineering Emerging Technologies, University of Tabriz, Tabriz, Iran
Ali Eslami
Affiliation:
Biomechatronics Laboratory, School of Engineering Emerging Technologies, University of Tabriz, Tabriz, Iran
Saeid Karimian Eghbal
Affiliation:
Biomechatronics Laboratory, School of Engineering Emerging Technologies, University of Tabriz, Tabriz, Iran
*
*Corresponding author. E-mail: azimirad@tabrizu.ac.ir
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Summary

In this paper an optimal path planning method based on a new evolutionary algorithm is presented for higher order robotic systems. It is a combination of immune system and wavelet mutation. By increasing the system's dimensions, the complexity of algorithm grows linearly. The obtained results have been compared with other optimal path producing algorithms, and its excellence in terms of optimality has been proved. Strengths of this method are simplicity in large-scale path planning, being free of most of the common deadlocks in usual method, and ability to obtain more optimized results than other similar methods. The effectiveness of this approach on simulation case studies for a three-link planar robot and 5 degrees of freedom mobile manipulators as well as an experiment for a mobile robot called K-joniour is shown.

Keywords

Artificial immune systemWaveletPath planningLarge-scale robots
Type
Articles
Information
Robotica , Volume 32 , Issue 1 , January 2014 , pp. 77 - 95
Copyright
Copyright © Cambridge University Press 2013 

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