摘要
现阶段A^(*)算法所规划路径存在转折点较多、直角弯处距离障碍过近等问题。针对军队车场巡检移动机器人执行任务需具备自主安全性的要求,提出一种基于改进的安全A^(*)与动态窗口法(DWA)融合的路径规划方法。首先,引入用于度量机器人安全性的危险指数(DI)指标,通过结合危险指数重新定义A^(*)算法的估价函数;同时,将搜索邻域扩展并去除同方向冗余子节点,从8邻域搜索优化到16邻域搜索,提高搜索效率,减少转折点个数;最后,扩展动态窗口法的路径融合评价函数,提升机器人局部避障能力。实验结果表明,所提安全A^(*)算法能够有效降低直角弯处碰撞风险,在运行时间、转折点数、规划路径上较传统A^(*)算法和已有方法有较明显优势;通过在仿真环境和真实环境下验证,所提融合方法均保障了机器人自主运行的安全性,符合军队车场巡检机器人作业需求。
At present, the path planned by A^(*)algorithm has many problems, such as many turning points, too close to obstacles at right angle bends and so on. Aiming at the requirement of autonomous security for military inspection mobile robot, a path planning method based on improved security A^(*)and dynamic window approach(DWA) is proposed. Firstly, the danger index(DI) is introduced to measure the safety of robot, and the evaluation function of A^(*)algorithm is redefined by combining the danger index. At the same time, the search neighborhood is expanded and the redundant sub nodes in the same direction are removed, and the search efficiency is improved and the number of turning points is reduced by optimizing the search neighborhood from 8 to 16. Finally, the path fusion evaluation function of dynamic window approach is extended to improve the local obstacle avoidance ability of robot.The experimental results show that the proposed safety A^(*)algorithm can effectively reduce the risk of corner collision, and has obvious advantages over traditional A^(*)algorithm and existing methods in running time, turning points and path planning. Through the verification in the simulation environment and real environment, the proposed fusion method ensures the safety of autonomous operation of the robot, and meets the requirements of inspection robot in military depot.
作者
金梅
李清天
张立国
JINMei;LIQingtian;ZHANGLiguo(SchoolofElectricalEngineering,YanshanUniversity,Qinhuangdao066000)
出处
《高技术通讯》
CAS
2022年第11期1202-1212,共11页
Chinese High Technology Letters
基金
河北省军民融合产业发展专项(2018B190)资助项目。
