Abstract: To solve the problems of traditional A* algorithm and dynamic window approach in mobile robot path planning,the optimization schemes of two algorithms and fusion scheme of optimization algorithms were proposed.To solve the problem of strong route symmetry and many redundant points in traditional A* algorithm,parent node information was introduced to reconstruct cost function that could dynamically adjust heuristic function weight,and a key point extraction strategy was designed.To solve the problem of lengthy route in traditional dynamic window approach,the obstacle distance evaluation sub-function was improved,and a self-adaptive-environment improvement strategy of dynamic window approach was proposed.Aiming at the problem of unreachable-target-point and low security about improved DWA algorithm and optimized A* algorithm,the optimized A* algorithm and improved dynamic window approach were combined,and a new global path evaluation sub-function was designed.Finally,simulation and experiment results showed that the fusion algorithm had greatly improved in planning efficiency,safety and path smoothness,and more aligned with motion characteristics of mobile robots.

Key words: mobile robot, path planning, A* algorithm, dynamic window approach, algorithm fusion

摘要： 为解决传统A*算法和动态窗口法在移动机器人路径规划中出现的问题,提出了两种算法的优化方案和优化算法的融合方案。首先,针对传统A*算法中路线对称性强、冗余点多的问题,在启发函数中引入父节点信息,重新构建了可动态调节启发函数权重的代价函数,设计了关建点提取策略。其次,针对传统动态窗口法路线冗长的问题,改进了障碍物距离评价子函数,提出了动态窗口法的自适应环境改进策略。然后,针对改进动态窗口法存在目标点不可达和优化A*算法安全性低的问题,融合了优化A*算法和改进动态窗口法,设计了新的全局路径评价子函数。最后,通过仿真和实验结果对比,验证了融合算法在规划效率、安全性和路径平滑性等方面有很大提升,更符合移动机器人的运动特性。

关键词: 移动机器人, 路径规划, A*算法, 动态窗口法, 算法融合