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Path Planning of Composite Trackless AGV Considering Map Preprocessing*

机译:考虑地图预处理的综合磁干agv路径规划*

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With mounted robot arm, the compound trackless automatic guided vehicle (AGV) has strong flexibility and adaptability in industrial environments. However, due to the space constraints of the robot arm, the path planning in complex large scenes is hard to achieve high efficiency, and it is easy for falling into local minimum and stagnation. In this paper, a novel AGV path planning algorithm is proposed on the basis of map preprocessing to improve the planning efficiency and guarantee operating safety. First, by integrating the multiple constraints including the obstacles and robotic position/posture, the preprocessing method of the environmental map is proposed utilizing obstacle expansion and Delaunay triangulation. Then, to achieve better convergence and global optimization capacity, the global path searching is modified by (1) constructing the OpenList with priority queues; (2) exploring the adaptive rules for step size and dynamic weighted heuristic function. Finally, combining linearization and cubic Hermite interpolation method, the planned path is smoothed to enhance the movement stability and energy consumption rate. Simulation analysis and experimental results verify the feasibility, efficiency and superiority of the proposed path planning method.
机译:随着安装的机器人臂,复合轨道自动引导车辆(AGV)具有强大的灵活性和工业环境的适应性。然而,由于机器人臂的空间限制,复杂大型场景中的路径规划很难实现高效率,并且很容易落入局部最小和停滞状态。本文在地图预处理的基础上提出了一种新颖的AGV路径规划算法,以提高规划效率和保证操作安全性。首先,通过集成包括障碍物和机器人位置/姿势的多个约束,利用障碍物扩张和Delaunay三角测量来提出环境图的预处理方法。然后,为了实现更好的收敛和全局优化容量,通过(1)构建具有优先级队列的OpenList的(1)修改全局路径搜索; (2)探索步骤尺寸和动态加权启发式功能的自适应规则。最后,结合线性化和立方Hermite插值方法,平滑计划路径以增强运动稳定性和能量消耗率。仿真分析和实验结果验证了所提出的路径规划方法的可行性,效率和优越性。

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