Global Path Planning Based on Steering Characteristics of Tracked Robot
Traditional A-star path planning algorithm ignored vehicle steering process,which led to a lon-ger travel time for the planned path.To solve this problem,this paper proposed an improved A-star algo-rithm 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 character-istics 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 con-structed 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 al-gorithm 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.
万方数据
维普
