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A motion planner for nonholonomic mobile robots

机译:非完整移动机器人的运动计划器

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This paper considers the problem of motion planning for a car-like robot (i.e., a mobile robot with a nonholonomic constraint whose turning radius is lower-bounded). We present a fast and exact planner for our mobile robot model, based upon recursive subdivision of a collision-free path generated by a lower-level geometric planner that ignores the motion constraints. The resultant trajectory is optimized to give a path that is of near-minimal length in its homotopy class. Our claims of high speed are supported by experimental results for implementations that assume a robot moving amid polygonal obstacles. The completeness and the complexity of the algorithm are proven using an appropriate metric in the configuration space R/sup 2//spl times/S/sup 1/ of the robot. This metric is defined by using the length of the shortest paths in the absence of obstacles as the distance between two configurations. We prove that the new induced topology and the classical one are the same. Although we concentrate upon the car-like robot, the generalization of these techniques leads to new theoretical issues involving sub-Riemannian geometry and to practical results for nonholonomic motion planning.
机译:本文考虑了类似汽车的机器人(即具有非完整约束且转弯半径较低的移动机器人)的运动计划问题。我们为移动机器人模型提供了一种快速而精确的计划器,它是基于低级几何计划器忽略运动约束而生成的无碰撞路径的递归细分。优化所得的轨迹,以给出在同伦类中接近最小长度的路径。我们的高速声称得到了实验结果的支持,这些实验结果假设实施机器人在多边形障碍物之间移动。使用机器人的配置空间R / sup 2 // spl times / S / sup 1 /中的适当度量,证明了算法的完整性和复杂性。通过使用没有障碍物的最短路径的长度作为两个配置之间的距离来定义此度量。我们证明了新的诱导拓扑和经典的诱导拓扑是相同的。尽管我们专注于类似汽车的机器人,但是这些技术的泛化导致涉及亚黎曼几何的新理论问题以及非完整运动规划的实际结果。

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