The STL motion-planning problem is reformulated as a shortest-path problem over a graph of convex sets to generate smooth Bézier-spline trajectories satisfying logical, timing, smoothness, and velocity constraints.
Faster algorithms for growing collision-free convex polytopes in robot configuration space
2 Pith papers cite this work. Polarity classification is still indexing.
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Neural CDF barriers enable efficient planning and distributionally robust safe control for manipulators in cluttered dynamic environments using only point-cloud observations.
citing papers explorer
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Signal Temporal Logic Motion Planning via Graphs of Convex Sets
The STL motion-planning problem is reformulated as a shortest-path problem over a graph of convex sets to generate smooth Bézier-spline trajectories satisfying logical, timing, smoothness, and velocity constraints.
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Neural Configuration-Space Barriers for Manipulation Planning and Control
Neural CDF barriers enable efficient planning and distributionally robust safe control for manipulators in cluttered dynamic environments using only point-cloud observations.