Article

Shape-Aware Neural Time Fields: Physics-Informed Neural Time Fields for Rigid-Body Motion and Manipulation Planning

We propose Shape-Aware Neural Time Fields, a physics-informed neural motion planning framework that learns a reusable travel-time (cost-to-go) representation for rigid-body motion, explicitly distinguishing the different geometric constraints on translation and rotation, and pairs it with a sampling-based planner.

Part of the event: Proposing Shape-Aware Neural Time Fields for Rigid Body Motion Planning

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