基于改进A^(*)算法和Bezier曲线的多机协同全局路径规划

Multi-machine Cooperation Global Path Planning Based on A-star Algorithm and Bezier Curve

为了实现农田作业环境下的多机协同导航作业的远程调度管理,开展了基于改进A^(*)算法和Bezier曲线的全局路径规划研究。阐述了农田作业环境下的多机协同路径规划,多机协同路径规划分为全局路径规划和局部动态避障;利用改进A^(*)算法实现了全局路径寻优和拐角优化,并基于Bezier曲线对全局路径进行了平滑处理;根据随机生成的障碍物环境地图和涿州试验农场环境地图,利用Matlab平台分别对全局路径规划算法进行了仿真试验。仿真结果表明,通过调节改进A^(*)算法中的权重w(n),搜索效率得到了明显提高,基于涿州试验农场的仿真试验中,优化后算法运行时间为0.832 s;通过对全局路径进行拐角优化,在路径长度相近的情况下,有效降低了转弯次数;同样,利用Bezier曲线进行路径平滑后,拐角处的尖峰得到了优化,确保农机在实际农田作业中平稳行进,初步满足了实时性和平滑性需求,为实现农田作业环境下的多机协同路径规划提供了基础。

In order to realize the remote dispatching management of multi-machine cooperative navigation operation in complex farmland environment,the research of global path planning based on improved A-star algorithm and Bezier curve was carried out.Multi-machine cooperative operation path planning in farmland operation environment was introduced,which was divided into global path planning and local dynamic obstacle avoidance;The improved A-star algorithm was used to optimize the global path and corner optimization,and the global path was smoothed based on Bezier curve;According to the randomly generated obstacle environment map and Zhuozhou Experimental Farm environment map,the multi-machine cooperative global path planning algorithm was simulated by using Matlab platform.The simulation results showed that by adjusting the value of weight w(n)in the improved A-star algorithm,the search efficiency was significantly improved,the running time of the optimized algorithm was 0.832 s in the simulation experiment based on Zhuozhou Experimental Farm.Through corner optimization,the number of turns was effectively reduced when the path length was similar.Similarly,after using Bezier curve to smooth the path,the peak at the corner was well optimized to ensure the smooth progress of agricultural machinery in the actual farmland operation,which preliminarily met the real-time and smooth requirements,and provided a basis for further solving the multi-machine cooperative path planning in the field environment.