An Optimized Random Tree and Particle Swarm Algorithm For Distribution Environments

• 발행기관: 한국유통과학회
• 저자명: Zhou Feng Un-Kon Lee
• 간행물 정보: 『유통과학연구(JDS)』제13권 제6호, 11~15쪽, 전체 5쪽
• 주제분류: 경제경영 > 경제학
• 파일형태: PDF
• 발행일자: 2015.06.30

영문 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.

목차

1. Introduction

2. Description of Environment

3. RRT-PSO

4. Simulation Result

5. Conclusion

References

키워드

Robot Path Planning Rapidly-exploring Random Tree Particle Swarm Optimizer