VAMP

Collision-free arm motion takes traditional sampling planners hundreds of milliseconds, too slow for real time. VAMP uses SIMD vector instructions to parallelize collision checking, bringing sampling-based motion planning down to microseconds.

From Rice University's Kavraki Lab, it has a C++ core, Python bindings and common arm models.

Features

SIMD:Parallel collision checks.

Microseconds:Real-time planning.

Python:Easy experiments.