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为了提高机器人路径规划的速度,提出一种全新的机器人路径规划算法.算法中,青蛙以随机方式和启发方式两种策略从可选栅格集中选择栅格.子蛙群进行更新时,最坏青蛙根据与子群最优青蛙或全局最优青蛙的路径交点栅格更新路径.为了进一步提高搜索速度,算法中引入评分法,只对得分小于阈值的青蛙进行更新,同时采用双种群双向搜索的方法.大量仿真实验结果表明,该算法比同类算法的收敛速度提高数十倍以上,能在复杂的静态障碍环境中,迅速规划出一条安全避碰的优化路径.
In order to improve the speed of robot path planning, a new algorithm for robot path planning is proposed, in which the frog selects grids from a set of selectable grids in a random and enlightened manner, and when the frogs are updated, the worst In order to further improve the search speed, the algorithm introduced a scoring method, which only updates the frogs whose score is less than the threshold value, and uses the bidirectional search method of double population The results of a large number of simulation experiments show that the convergence speed of this algorithm is more than several tens of times higher than that of the same algorithm, and a safe collision avoidance optimization path can be rapidly planned in complicated static obstacle environment.