改进麻雀算法和A*算法的农业机器人路径规划

Path Planning Method of Agricultural Robot Based on A*Algorithm and Improved Sparrow Search Algorithm

针对农业机器人在复杂未知的农业生产环境中,避障能力差,路径规划欠优,折点较多的问题,提出一种基于改进麻雀搜索算法和A*算法相结合的A*-ISSA路径规划策略。首先,提出一种自适应多普勒发现者搜索策略,用于平衡算法的全局勘探能力和局部开发能力。通过量子行为对加入者位置更新方式进行改进,提出量子加入者位置更新策略,提高麻雀搜索算法的局部开发能力,防止算法陷入局部最优。其次,通过A*算法对启发函数进行全局规划,得到机器人运行的主路径,并通过改进的麻雀搜索算法对主路径进行二次规划,得到农业机器人最终的作业路径。最后,将所得实验结果与其他几类农业机器人路径规划策略的实验结果进行对比验证。实验结果表明,与其他优化策略相比,A*-ISSA求解时间最短,工作路径最短,折点数最少。

Aiming at the problems of poor obstacle avoidance ability,poor path planning and too many break points of agricultural robot in complex and unknown agricultural production environment,an A*-ISSA path planning strategy based on improved sparrow search algorithm and A*algorithm is proposed.Firstly,an adaptive Doppler finder search strategy is proposed to balance the global exploration capability and local development capability of the algorithm.In order to improve the sparrow search algorithm's ability of local development and prevent the algorithm from flling into local optimum,the quantum behavior is used to improve the way of updating the position of the participant.Secondly,the heuristic function is globally planned by A*algorithm to obtain the main path of the robot,and the improved sparrow search algorithm is used for quadratic planning of the main path to obtain the final operation path of the agricultural robot.Finally,the experimental results are compared with those of other path planning strategies.The experimental results show that,compared with other optimization strategies,A*-ISSA has the shortest solution time,the shortest working path and the least number of break points.