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Modified robust panel method for mobile robot path planning in partially unknown static and dynamic environments

机译:用于部分未知静态和动态环境的移动机器人路径规划的改进鲁棒面板方法

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This paper proposes a novel panel method, called modified robust panel method (MRPM), useful to represent open polygonal chains. MRPM extends an existing panel method approach in order to account for moving obstacles. It is effective for the mobile robot path planning in both static and dynamic environments under partially unknown conditions satisfying real-time requirements. The robustness of the method lays in automatically adjusting the potential field parameters based on the obstacle shapes and sizes taking in account all field segments. These parameters need to be limited so that convergence to the goal position is guaranteed. An activation window and an algorithm to select the relevant obstacles are also presented in order to reduce the computation time. The modified Histogramic-In-Motion-Map (HIMM) algorithm is used to continuously update a grid-based map in which each cell stores the probability of the related region that is occupied by an obstacle. In order to verify the proposed methods a three-layered robot navigation system is developed. The effectiveness and robustness of the proposed methods are demonstrated through simulations.
机译:本文提出了一种新颖的面板方法,称为改进鲁棒面板方法(MRPM),可用于表示开放式多边形链。 MRPM扩展了现有的面板方法,以解决移动障碍。对于满足实时要求的部分未知条件下的静态和动态环境中的移动机器人路径规划,它非常有效。该方法的鲁棒性在于考虑障碍物的形状和大小,并考虑所有视野段,自动调整潜在的视野参数。需要限制这些参数,以确保收敛到目标位置。为了减少计算时间,还介绍了激活窗口和选择相关障碍物的算法。修改后的直方图运动地图(HIMM)算法用于连续更新基于网格的地图,其中每个单元格存储障碍物占据的相关区域的概率。为了验证所提出的方法,开发了三层机器人导航系统。通过仿真证明了所提方法的有效性和鲁棒性。

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