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1. Path planning algorithm for mobile robot obstacle avoidance adopting Bezier curve based on Genetic Algorithm

Author

Tang Zhonghua, Lv Weixian, Luo Zhongwen, and Yang Linquan

Subjects
Mathematical optimization, Fitness function, Path length, Obstacle avoidance, Genetic algorithm, Path (graph theory), Robot, Mobile robot, Motion planning, Algorithm, ComputingMethodologies_COMPUTERGRAPHICS, Mathematics
Abstract

Combining the Genetic Algorithm and Bezier curve, a new path planning for mobile robot is presented. This path replaces the traditional broken lines with smooth Bezier curve. Therefore it can satisfy the non-holonomic constraints of two-wheel-robot model and serves also the mobile robot rather ideal acceleration. Then it searches the optimal time-cost for control points of Bezier that stands for the path with Genetic Algorithm. The fitness function of Genetic Algorithm takes 3 factors that influence the moving time of robot seriously: security, length and smoothness of the path. The results of simulation and real competitions showed its good effectiveness.

Published
2008

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