融合改进蚁群和DWA的移动机器人路径规划

Path Planning of Mobile Robot Based on Improved Ant Colony and DWA

针对传统蚁群算法搜索时间长、易陷入局部最优且动态规划能力弱等缺陷,提出一种融合改进蚁群和动态窗口算法(DWA,Dynamic Window Approach)的路径规划方法,解决移动机器人全局路径优化以及局部动态避障路径规划问题。在分析传统蚁群算法路径规划原理及优缺点的基础上,通过引入初始栅格转移规则、改变信息素更新方式、删除冗余节点、圆切障碍顶点等方法,提高蚁群算法的收敛速度、规划路径的平滑度以及安全可靠度;进一步在改进蚁群算法中引入DWA进行局部路径规划,实现机器人的动态避障。对比仿真结果表明,所提改进算法在路径长度、迭代次数、收敛时间以及路径平滑度、安全可靠度等性能指标上较传统算法均有所提高。

Aiming at the shortcomings of traditional ant colony algorithm such as long search time,easy to fall into local optimum and weak dynamic planning ability,a path planning method combining improved ant colony algorithm and dynamic window approach(DWA)is proposed to solve the global path optimization and local dynamic obstacle avoidance path planning problems of mobile robot.Based on the analysis of the traditional ant colony algorithm path planning principle and its advantages and disadvantages,by introducing the initial grid transfer rules,changing the pheromone update mode,deleting redundant nodes,circle tangent obstacle vertices and other methods,the convergence speed,smoothness and safety reliability of the ant colony algorithm are improved.Furthermore,DWA is introduced into the improved ant colony algorithm for local path planning,which is proved to be effective it introduces the dynamic obstacle avoidance of robot.The simulation results show that the improved algorithm has better performance than the traditional algorithm in path length,iteration times,convergence time,path smoothness,security and reliability.