Reproduce “Reachable Sets for Safe, Real-Time Manipulator Trajectory Design” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Patrick Holmes, Shreyas Kousik, Bohao Zhang, Daphna Raz, Corina Barbalata, Matthew Johnson-Roberson, Ram Vasudevan
The Autonomous Reachability-based Manipulator Trajectory Design (ARMTD) method enables real-time, provably safe motion planning for high-dimensional robotic arms. This approach achieves a 0% crash rate in complex simulations and hardware demonstrations by constructing conservative reachable sets from lower-dimensional joint reachable sets and integrating them into an optimization framework.
Key insights
- High-dimensional workspace reachable sets for robotic manipulators can be tractably and conservatively approximated by composing lower-dimensional joint reachable sets, overcoming the traditional 'curse of dimensionality' for such systems.
- Sub-differentiable safety constraints, derived from these time-varying reachable sets, can be effectively incorporated into a real-time trajectory optimization problem, enabling mathematically provable collision avoidance.
- A receding-horizon framework with a guaranteed fail-safe mechanism ensures continuous safety; if a new safe plan cannot be found, a predefined safe maneuver from the previous iteration is executed.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.