考虑履带机器人转向特性的全局路径规划

Global Path Planning Based on Steering Characteristics of Tracked Robot

针对传统A星路径规划算法忽略车辆转向过程,导致规划路径行程时间较长的问题,提出了考虑履带车转向特性的改进A星算法。首先,扩大A星算法的搜索邻域,提高转向角的灵活度。其次,分析考虑履带车的转向特性,将转向时间加入到代价函数中,建立以时间最短为目标的代价函数,缩短履带车的行程时间。最后,构建删除冗余节点和新增优化节点的规则,改善路径的平滑性使规划的路径进一步优化。通过Matlab仿真和实车实验进行研究,研究结果表明:改进算法在路径长度、转向次数和行驶时间方面都有了减少,规划的路径要优于传统A星算法和对比文献算法。改进A星算法能有效提高所规划路径的质量,提升履带机器人的自主巡航能力和智能化水平。

Traditional A-star path planning algorithm ignored vehicle steering process,which led to a longer travel time for the planned path.To solve this problem,this paper proposed an improved A-star algorithm considering the steering characteristics of tracked vehicles.Firstly,this study expanded the search space of the A-star algorithm to improve the flexibility of steering angle.Secondly,the steering characteristics of the tracked vehicle were analyzed and considered,and the steering time was added to the cost function.A cost function with the shortest time as the goal was established to shorten the travel time of the tracked vehicle.Finally,the rules for deleting redundant nodes and adding optimized nodes were constructed to improve the smoothness of the path and further optimize the planned path.The research was carried out through Matlab simulation and real vehicle experiment.The results show that the improved algorithm has reduced the path length,steering times,and travel time.The path planned by the algorithm proposed in this paper is superior to those of the traditional A-star algorithm and the compared literature algorithm.The improved A-star algorithm proposed in this study can effectively improve the quality of the planned path,improve the autonomous cruising ability and intelligence level of the tracked robot,and has important reference value for the development of the tracked robot.