Path planning algorithm for mobile robot obstacle avoidance adopting Bezier curve based on Genetic Algorithm
Yang Linquan, Luo Zhongwen, Tang Zhonghua, LV Wei-xian · 2008
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.