逐次多様体上のサンプリングベース運動計画
Sampling-Based Motion Planning on Sequenced Manifolds
制約が運動中に変化する環境を交差する多様体の列として定式化し、RRT*を内側ループに用いたPSM*アルゴリズムで最適な交差点を探索する手法を提案した論文。
著者: Peter Englert, Isabel M. Rayas Fernández, Ragesh K. Ramachandran, Gaurav S. Sukhatme
分類: cs.RO, cs.CG
原文アブストラクト
We address the problem of planning robot motions in constrained configuration spaces where the constraints change throughout the motion. The problem is formulated as a fixed sequence of intersecting manifolds, which the robot needs to traverse in order to solve the task. We specify a class of sequential motion planning problems that fulfill a particular property of the change in the free configuration space when transitioning between manifolds. For this problem class, we develop the algorithm Planning on Sequenced Manifolds (PSM*) which searches for optimal intersection points between manifolds by using RRT* in an inner loop with a novel steering strategy. We provide a theoretical analysis regarding PSM*s probabilistic completeness and asymptotic optimality. Further, we evaluate its planning performance on multi-robot object transportation tasks. Video: https://youtu.be/Q8kbILTRxfU Code: https://github.com/etpr/sequential-manifold-planning
