Sampling-Based Motion Planning on Sequenced Manifolds
Peter A. J. Englert, Isabel M. Rayas Fernández, Ragesh Kumar Ramachandran, Gaurav S. Sukhatme · 2021
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, the algorithm Planning on Sequenced Manifolds (PSM * ) is developed 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.