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Research on path planning of quadruped robot based on globally mapping localization

机译:基于全局映射定位的四足机器人路径规划研究

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Perception and navigation control is core key technology for the legged robot to adapt to complex terrain and achieve autonomous walking. It is the key to distinguish the legged robot from manned equipment and become a ground unmanned system. In this paper, the SLAM globally localization system based on the lidar point cloud is established, and a localization framework based on the combination of topological measurements is proposed to realize the map reconstruction and localization of the wild environment. Path planning based on Dijkstra algorithm is proposed to implement the globally terrain autonomous navigation task of the quadruped robot, and autonomous obstacle avoidance strategy of the local map for quadruped robot based on the artificial potential field theory is applied considering the motion and vibration of legged robot. The experimental results show that the globally path navigation can accurately plan the optimal path and complete the autonomous obstacle avoidance of the local map. The results have demonstrated the effectiveness of the proposed method and realize the globally field autonomous walking of the quadruped robot.
机译:感知和导航控制是腿部机器人的核心关键技术,适应复杂地形并实现自主行走。将腿部机器人与载人设备区分开并成为地面无人体系的关键。在本文中,基于激光雷达点云的SLAM全球定位系统的建立,以及基于拓扑测量的组合本地化框架,提出了实现地图重建和本地化的野生环境。基于Dijkstra算法的路径规划,以实现基于人工势势场理论的基于四足机器人的全球地形机器人自主导航任务,以及基于人工势势场理论的四足机器人的局部地图的自主障碍避免策略应用于腿机器人的运动和振动。实验结果表明,全球路径导航可以准确地规划最佳路径并完成本地地图的自主障碍物。结果表明了提出的方法的有效性,并实现了四足机器人的全球场自主行走。

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