유통과학연구 (Journal of Distribution Science)
- 제13권6호
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- Pages.11-15
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- 2015
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- 1738-3110(pISSN)
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- 2093-7717(eISSN)
DOI QR Code
An Optimized Random Tree and Particle Swarm Algorithm For Distribution Environments
- Feng, Zhou (College of Electronic Information, Shandong Institute of Commerce and Technology, Economic and Business Administration, The University of Suwon) ;
- Lee, Un-Kon (School of Economic and Business Administration, The University of Suwon)
- 투고 : 2015.02.19
- 심사 : 2015.06.14
- 발행 : 2015.06.30
초록
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.