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Sampling-Based Motion Planning on Manifold Sequences

by   Peter Englert, et al.

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 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 Sequential Manifold Planning (SMP*) is developed that 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 SMP*s probabilistic completeness and asymptotic optimality. Further, we evaluate its planning performance on various multi-robot object transportation tasks.


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