机器人运动规划和真实几何的一种新的代数方法

J. Canny
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引用次数: 118

摘要

提出了一种求解单指数序列时间内的寻径问题或广义移动问题的算法。这是第一个求解序列时间界小于双指数问题的算法。实际上,该算法的组合指数等于自由度的个数,使其成为最坏情况下的最优算法,并等于或改进了许多专用算法的时间界限。该算法接受描述自由构型集合的半代数集合S的公式,并产生该集合的一维骨架或“路线图”,该骨架或“路线图”连接在S的每个连接分量内。附加的点可以在线性时间内连接到路线图。我们的方法借鉴了奇点理论的结果,特别是利用了分层集的概念作为单元分解的有效替代。引入了多元结式的代数工具,给出了齐次多项式方程组有解的充分必要条件,并证明了它可以在多项式并行时间内计算。这一结果的结果包括量词消去的新方法和多项式系统根绝对值的改进间隙定理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new algebraic method for robot motion planning and real geometry
We present an algorithm which solves the findpath or generalized movers' problem in single exponential sequential time. This is the first algorithm for the problem whose sequential time bound is less than double exponential. In fact, the combinatorial exponent of the algorithm is equal to the number of degrees of freedom, making it worst-case optimal, and equaling or improving the time bounds of many special purpose algorithms. The algorithm accepts a formula for a semi-algebraic set S describing the set of free configurations and produces a one-dimensional skeleton or "roadmap" of the set, which is connected within each connected component of S. Additional points may be linked to the roadmap in linear time. Our method draws from results of singularity theory, and in particular makes use of the notion of stratified sets as an efficient alternative to cell decomposition. We introduce an algebraic tool called the multivariate resultant which gives a necessary and sufficient condition for a system of homogeneous polynomials to have a solution, and show that it can be computed in polynomial parallel time. Among the consequences of this result are new methods for quantifier elimination and an improved gap theorem for the absolute value of roots of a system of polynomials.
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