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ISSN : 1738-3110

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Early Access e-Submission

Vol.13 No.6

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An Optimized Random Tree and Particle Swarm Algorithm For Distribution Environments

The Journal of Distribution Science / The Journal of Distribution Science, (P)1738-3110; (E)2093-7717
2015, v.13 no.6, pp.11-15
https://doi.org/https://doi.org/10.15722/jds.13.6.201506.11
Feng, Zhou
Lee, Un-Kon
Feng,, Z. , & Lee,, U. (2015). An Optimized Random Tree and Particle Swarm Algorithm For Distribution Environments. The Journal of Distribution Science, 13(6), 11-15, https://doi.org/https://doi.org/10.15722/jds.13.6.201506.11

Abstract

Purpose - Robot path planning, a constrained optimization problem, has been an active research area with many methods developed to tackle it. This study proposes the use of a Rapidly-exploring Random Tree and Particle Swarm Optimizer algorithm for path planning. Research design, data, and methodology - The grid method is built to describe the working space of the mobile robot, then the Rapidly-exploring Random Tree algorithm is applied to obtain the global navigation path and the Particle Swarm Optimizer algorithm is adopted to obtain the best path. Results - Computer experiment results demonstrate that this novel algorithm can rapidly plan an optimal path in a cluttered environment. Successful obstacle avoidance is achieved, the model is robust, and performs reliably. The effectiveness and efficiency of the proposed algorithm is demonstrated through simulation studies. Conclusions - The findings could provide insights to the validity and practicability of the method. This method makes it is easy to build a model and meet real-time demand for mobile robot navigation with a simple algorithm, which results in a certain practical value for distribution environments.

keywords
Robot, Path Planning, Rapidly-exploring, Random Tree Particle, Swarm Optimizer

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