Tangent Space RRT with Lazy Projection: An Efficient Planning Algorithm for Constrained Motions
Rapidly-Exploring Random Trees (RRT) have been successfully used in motion planning problems involving a wide range of constraints. In this paper we develop a more robust and efficient version of the constrained RRT planning algorithm of . The key idea is based on first constructing RRTs on tangent space approximations of constraint manifold, and performing lazy projections to the constraint manifold when the deviation exceeds a prescribed threshold. Our algorithm maintains the Voronoi bias property characteristic of RRT-based algorithms, while also reducing the number of projections. Preliminary results of a numerical study, together with a discussion of the potential strengths and weaknesses of our algorithm, are presented.
Key wordsRapidly-exploring random tree constrained motion planning lazy projection
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