Differentially constrained motion replanning using state lattices with graduated fidelity
Differentially constrained motion replanning using state lattices with graduated fidelity
复制标题
使用具有分级保真度的状态格进行差分约束运动重新规划
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
A. Kelly
中科院分区：
文献类型：
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作者：
M. Pivtoraiko;A. Kelly
本文提出了一种差分约束机器人运动规划和有效的重新规划的方法。微分约束的满足是由状态格保证的，状态格是一个由满足构造约束的运动组成的搜索空间。可以利用任何系统的重新规划算法（例如D*）来搜索状态网格以找到满足微分约束的运动规划，并且在环境改变的情况下有效地修复它。通过改变规划问题的表示的保真度来获得进一步的效率。高保真度在最重要的地方使用，而在不会显著影响计划质量的地方则会降低。本文提出了一种方法来修改replans之间的保真度，从而使搜索空间的动态灵活性，同时保持其与重新规划算法的兼容性。该方法特别适合于在未知的具有挑战性的环境中的移动的机器人应用。在这种情况下，我们成功地应用规划的导航研究原型漫游车在喷气推进实验室火星院子里。
This paper presents an approach to differentially constrained robot motion planning and efficient re-planning. Satisfaction of differential constraints is guaranteed by the state lattice, a search space which consists of motions that satisfy the constraints by construction. Any systematic replanning algorithm, e.g. D*, can be utilized to search the state lattice to find a motion plan that satisfies the differential constraints, and to repair it efficiently in the event of a change in the environment. Further efficiency is obtained by varying the fidelity of representation of the planning problem. High fidelity is utilized where it matters most, while it is lowered in the areas that do not affect the quality of the plan significantly. The paper presents a method to modify the fidelity between replans, thereby enabling dynamic flexibility of the search space, while maintaining its compatibility with replanning algorithms. The approach is especially suited for mobile robotics applications in unknown challenging environments. In this setting, we applied the planner successfully to the navigation of research prototype rovers in JPL Mars Yard.