论文标题
内部方法解决运动计划问题的狭窄通道
An Interior Point Method Solving Motion Planning Problems with Narrow Passages
论文作者
论文摘要
针对运动计划问题的算法解决方案已经研究了五十年。自1969年的A发展以来，已经研究了许多方法，传统上被归类为网格分解，潜在的领域或基于抽样的方法。在这项工作中，我们专注于使用数值优化，该优化被研究用于解决运动计划问题。这种对基于抽样方法的利益缺乏兴趣很大程度上是由于狭窄段落引入的非跨性别性。我们通过将解决方案接地差异几何形状来解决这一缺点。我们通过一系列实验在3个DOF和6个DOF狭窄的通道问题上进行了证明，如何显式建模基础的Riemannian歧管会导致有效的内点非线性编程解决方案。
Algorithmic solutions for the motion planning problem have been investigated for five decades. Since the development of A* in 1969 many approaches have been investigated, traditionally classified as either grid decomposition, potential fields or sampling-based. In this work, we focus on using numerical optimization, which is understudied for solving motion planning problems. This lack of interest in the favor of sampling-based methods is largely due to the non-convexity introduced by narrow passages. We address this shortcoming by grounding the solution in differential geometry. We demonstrate through a series of experiments on 3 Dofs and 6 Dofs narrow passage problems, how modeling explicitly the underlying Riemannian manifold leads to an efficient interior-point non-linear programming solution.
