融合目标检测与DWA算法的AGV路径OA
Research on AGV Path Fusion of Object Detection and DWA Algorithm
针对AGV(Automated Guided Vehicle)叉车处于环境信息未知或环境动态变化情况下的路径规划及导航问题,文中提出了一种由YOLOv5(You Only Look Once version 5)目标检测算法获取目标位置.根据目标位置规划出全局基础路径,再融合DWA(Dynamic Window Approach)局部动态路径规划算法进行AGV路径规划与导航,使AGV叉车在未知环境或局部环境信息未知的环境中能快速识别目标位置并完成路径规划到达目标位置.实验结果表明,相较于改进前方法,文中所提方法在路径长度、耗费时间以及AGV叉车航向误差方面均有良好表现,路径长度平均减少 12%,耗费时间平均减少约5%且AGV航向与目标航向的平均误差在5°以内.所提方法提高了AGV叉车在未知环境中的工作效率以及工作灵活性.
In view of the path planning and navigation problem when the AGV forklift is in the situation of un-known environment information or dynamic change of environment,a method is proposed to obtain the target position by YOLOv5(You Only Look Once version 5)target detection algorithm.The global basic path is planned according to the target location,and the method of AGV path planning and navigation is integrated with DWA(Dynamic Win-dow Approach)local dynamic path planning algorithm,so that the AGV forklift can quickly identify the target loca-tion and complete the path planning to reach the target location in the unknown environment or the environment with unknown local environment information.The experimental results show that compared with the previous method,the proposed method has good performance in terms of path length,time consumption and heading error of AGV forklift truck.The average path length is reduced by 12%,the average time consumption is reduced by about 5%,and the average error between the AGV heading and the target heading is within 5°.The proposed method can improve the working efficiency and flexibility of AGV forklift in unknown environment.
李筠;刘虎;杨海马;王原;徐文成;黄宏欣
上海理工大学 光电信息与计算机工程学院,上海 200093
计算机与自动化
AGVYOLOv5DWA算法全局路径规划局部路径规划目标检测导航自动导引
AGVYOLOv5DWA algorithmglobal path planninglocal path planningtarget detectionnavigationautomatic guidance
《电子科技》 2024 (007)
33-42 / 10
中科院空间主动光电技术重点实验室开放基金(2021ZDKF4);上海市科委科技创新行动计划(21S31904200,22S31903700)Open Fund of the Key Laboratory of Space Active Optoelectronic Technology of the Chinese Academy of Sciences(2021ZDKF4);Shanghai Municipal Commission of Science and Technology Innova-tion Action Plan(21S31904200,22S31903700)
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