复杂环境下农业机器人路径规划优化方法

Optimization Method of Agricultural Robot Path Planning in Complex Environment

针对在室外复杂环境下作业的农业机器人存在因能量受限导致工作完成率降低的问题,提出了一种基于改进的启发式搜索的ECA~*路径规划算法,该算法可以在资源受限的情况下完成能量损耗最优路径的规划。首先,通过建立机器人距离-能量损耗模型,计算机器人移动行进的路程和损耗的能量,并对未来的路径和能耗趋势进行评估。然后,在传统A~*算法的基础上,将距离-能量损耗模型代入启发代价函数,通过搜索扩展子节点寻找最优路径。在每次迭代过程中,通过对比剔除处于劣势的路径,以保证算法的高效性。最后,通过设计仿真实验,将改进的ECA~*算法与传统的A~*算法搜索到路径的能量损耗进行对比,并在之后的改进算法中添加相应的能量约束进行计算。仿真结果表明,改进算法减少14. 87%能量消耗,验证了ECA~*算法的有效性。

Aiming at the problem that the mobile robot operating in complex outdoor environment reduced work completion rate due to energy limitation because of consume excessive energy when moving along the shortest paths on uneven terrains which often consisted of rapid elevation changes, an improved heuristic search algorithm called ECA^* algorithm was proposed, which can optimize energy loss of the path when resources were limited. Firstly, the distance traveled and the energy lost by the robot were calculated by the establishment of robot distance-energy loss model, which can also evaluate the future path and the energy consumption trend. Then, the distance-energy loss model was brought into the heuristic cost function based on the traditional A^* algorithm and the extended sub-node was searched for the optimal path. In each iteration process, the path at the disadvantage was eliminated by comparison to ensure the efficiency of the algorithm. Finally, the energy loss of different paths searched by the improved algorithm as well as the traditional A^* algorithm was compared though the design of simulation experiment. The improved algorithm can reduce the energy consumption by 14.87% through the simulated calculation which verified the effectiveness of the improved algorithm.