Sampling-Based Motion Planning under Kinematic Loop-Closure Constraints
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چکیده
Kinematic loop-closure constraints significantly increase the difficulty of motion planning for articulated mechanisms. Configurations of closed-chain mechanisms do not form a single manifold, easy to parameterize, as the configurations of open kinematic chains. In general, they are grouped into several subsets with complex and a priori unknown topology. Sampling-based motion planning algorithms cannot be directly applied to such closed-chain systems. This paper describes our recent work [7] on the extension of sampling-based planners to treat this kind of
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Kinematic loop-closure constraints significantly increase the difficulty of motion planning for articulated mechanisms. Configurations of closed-chain mechanisms do not form a single manifold, easy to parameterize, as the configurations of open kinematic chains. In general, they are grouped into several subsets with complex topology than cannot be globally parameterized. This paper presents a g...
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تاریخ انتشار 2004