基于改进A*算法的AGV路径研究

路径规划能力是AGV(Automated Guided Vehicle,自动导引运输车)系统智能化程度的体现。在众多算法中,A~*算法使用代价消耗估算方式达到较快的计算能力,被广泛应用于AGV的路径规划中,但仍存在局部最优的规划问题,规划的路径上存在冗余节点和较多不必要拐点。为减少运输路径中的总能耗,缩短路径总长度和减少AGV转弯次数,采用分裂和筛选的方案对传统A~*算法进一步优化,提出改进A~*算法,使其在实际工作环境中搜索更加迅速、考虑更加周密。在传统A~*算法基础上,在未知节点的启发函数里增加转弯权值,可以在计算规划过程中考虑转向所带来的消耗,从而减少转弯次数。使用任务分裂方案可以尽可能多地选择出较优路径,其中的最优解能够实现得转弯较少,展现出比较平滑的线路。基于Ubuntu下ROS系统版本进行仿真,对比实验结果表明,改进A~*算法在规划时间、总行程以及转弯消耗等方面都优于传统A~*算法,提升了AGV的实际运行效率,减少了AGV小车的耗能,可以缩短路径搜索规划时间,更符合工厂环境对AGV的需求。

Research on AGV Path Based on Improved A*Algorithm

The ability of path planning is the embodiment of intelligent AGV(Automated Guided Vehicle)system.A*algorithm uses the method of cost consumption estimation to achieve fast computing power among many algorithms,which is widely used in AGV path planning.However,it still has the problem of local optimal path planning,and there are redundant nodes and many unnecessary inflection points in the planned path.In order to reduce the total energy consumption in the transportation path,shorten the total length and reduce the turning times of AGV,the traditional A*algorithm is further optimized by using the splitting and screening scheme,and the improved A*algorithm is proposed to make its search faster and more thoughtful in the actual working environment.On the basis of the traditional A*algorithm,turn weight is added to the heuristic function of the unknown node,and the turning consumption can be considered in the calculation and path planning process,thus reducing turning times.The scheme of task splitting can be used to select as many optimal paths as possible,in which the optimal solution can achieve fewer turns and show a relatively smooth circuit.Simulation based on ROS under Ubuntu system version,the results of contrast experiment show that the improved A*algorithm is better than the traditional algorithm in terms of search time,total path travel and number of right-angle turns,which improved the actual operation efficiency of AGV,reduced the energy consumption of AGV,and it can shorten the time of the path search planning.Improved A*Algorithm is more suitable for AGV requirements in factory environment.