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Robot Global Path Planning Based on Improved Artificial Fish-Swarm Algorithm

Jiansheng Peng, Xing Li, Zhiqiang Qin, Guan Luo

Year
2013
Citations
7
Access
Open access

Abstract

In This study, a new artificial fish-swarm optimization, to improve the foraging behavior of artificial fish swarm algorithm is closer to reality in order to let the fish foraging behavior, increase a look at the link (search) ambient, after examining environment, artificial fish can get more status information of the surrounding environment. Artificial fish screened from the information obtained optimal state for the best direction of movement. Will improve the foraging behavior of artificial fish-swarm algorithm applied to robot global path planning, including the robot to bypass the analog obstacles selected three ways: go obstructions outside, go inside the obstacles, both away obstructions and went outside obstacles Thing achieve robot shortest path planning. Via the MATLAB software emulation test: the improved foraging behavior of artificial fish-swarm algorithm to improve the rapid convergence of the algorithm and stability, improve fish swarm algorithm to the adaptability of the robot global path planning.

Keywords

Swarm behaviourForagingEmulationRobotComputer scienceMotion planningSwarm roboticsConvergence (economics)Artificial intelligenceAdaptability

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