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为了实现在避障环境空间下移动机器人的平滑最优路径规划,提出了一种基于改进蜂群算法的三次Bezier曲线优化的路径规划方法。借助Bezier曲线描述路径,把路径规划问题转换为生成Bezier曲线有限个点的位置优化问题,并改进人工蜂群优化算法进行最优路径搜索。该改进算法在雇佣蜂的搜索阶段中引入个体当前最优值及随机向量,并选择新的选择概率函数,不仅加快算法的收敛速度,而且在一定程度上有利于保持种群多样性,防止算法陷入局部最优。仿真结果表明,该算法可以有效地进行平滑路径的无碰撞路径规划。
In order to realize the smooth optimal path planning of mobile robot in obstacle avoidance environment, a path planning method of cubic Bezier curve optimization based on improved bee colony algorithm is proposed. Bezier curve is used to describe the path, which transforms the path planning problem into a position optimization problem that generates a finite number of Bezier curves and improves the artificial bee colony optimization algorithm for optimal path search. The improved algorithm introduces individual current optimal value and random vector into the search phase of homing bee and chooses a new selection probability function, which not only speeds up the convergence of the algorithm, but also helps to maintain the diversity of the population to prevent the algorithm from falling into Local optimum. The simulation results show that this algorithm can effectively plan the collision-free path of smooth path.