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Path planning of mobile robot based on hybrid improved artificial fish swarm algorithm

Yi Zhang, Yuanhong Hua

发表年份
2018
引用次数
5
访问权限
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摘要

The artificial fish swarm algorithm is easy to fall into the local optimum for robot global path planning. A hybrid improved Artificial Fish Swarm Algorithm (HIAFSA) is proposed. Firstly, the sub-optimal path is determined by A* algorithm, and then the adaptive behavior of artificial fish swarm algorithm is improved based on the inertia weight factor, and the attenuation function <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>α</mml:mi></mml:math> is introduced to improve the visual range and moving step length of the artificial fish, balance the global path planning and local path planning, and further improve the convergence speed and quality of the solution. The experimental results show that the hybrid improved artificial fish swarm algorithm has been improved in avoiding local optimum, convergence speed and precision.

关键词

Swarm behaviourAlgorithmMotion planningConvergence (economics)InertiaComputer sciencePath (computing)Artificial neural networkFish <Actinopterygii>Local optimum

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