SOURCE-LINKED INTELLIGENCE
ReVAMP: Vector-Accelerated Motion Planning for Kinematically-Constrained Systems via Reparameterization
Robots often must satisfy one or more constraints during motion planning for real-world tasks. When such constraints reduce the valid configuration space to a measure-zero subset, sampling based planning algorithms require modifications to draw feasible samples. For many common end-effector constraints, parameterizations built on inverse kinematics (IK) provide an alternate formulation where the constraints are satisfied by construction, allowing directly sampling the feasible set. Despite their elegant approach, parameterized planners have remained slower than vector-accelerated implementatio
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-24T17:45:26.000Z
First collected: 2026-09-25T06:12:46.948Z. This is not the publication date.