论文标题
重新审视懒概率的路线图
Lazy Probabilistic Roadmaps Revisited
论文作者
论文摘要
本文介绍了经典懒惰的概率路线图算法（懒惰PRM）的修订，该算法是由PRM配对和新颖的分支和切割（BC）算法产生的。切割是动态生成的约束，这些约束在PRM选择的几何图上施加的最低成本路径。削减消除无法映射到满足适当定义运动学约束的平滑计划中的路径。我们通过在最低成本的路径上将花键拟合到顶点来生成候选平滑计划。使用最近提出的算法对计划进行验证，该算法将它们映射到有限的痕迹中，而无需选择固定的离散步骤。痕量元素准确地描述了计划交叉约束边界何时模型算术精度。我们使用我们最近提出的谷仓基准的方法评估了几个计划者，并报告了方法可扩展性的证据。
This paper describes a revision of the classic Lazy Probabilistic Roadmaps algorithm (Lazy PRM), that results from pairing PRM and a novel Branch-and-Cut (BC) algorithm. Cuts are dynamically generated constraints that are imposed on minimum cost paths over the geometric graphs selected by PRM. Cuts eliminate paths that cannot be mapped into smooth plans that satisfy suitably defined kinematic constraints. We generate candidate smooth plans by fitting splines to vertices in minimum-cost path. Plans are validated with a recently proposed algorithm that maps them into finite traces, without need to choose a fixed discretization step. Trace elements exactly describe when plans cross constraint boundaries modulo arithmetic precision. We evaluate several planners using our methods over the recently proposed BARN benchmark, and we report evidence of the scalability of our approach.
