16 citations · 27 across the 4 of their papers we have counts for
4 papers
Towards Learning Efficient Maneuver Sets for Kinodynamic Motion Planning
Aravind Sivaramakrishnan, Zakary Littlefield, Kostas E. Bekris
Planning for systems with dynamics is challenging as often there is no local planner available and the only primitive to explore the state space is forward propagation of controls.…
Probabilistic completeness of RRT for geometric and kinodynamic planning with forward propagation
Michal Kleinbort, Kiril Solovey, Zakary Littlefield +2
The Rapidly-exploring Random Tree (RRT) algorithm has been one of the most prevalent and popular motion-planning techniques for two decades now. Surprisingly, in spite of its centr…
Fast, Anytime Motion Planning for Prehensile Manipulation in Clutter
Andrew Kimmel, Rahul Shome, Zakary Littlefield +1
Many methods have been developed for planning the motion of robotic arms for picking and placing, ranging from local optimization to global search techniques, which are effective f…
Asymptotically Optimal Sampling-based Kinodynamic Planning
Yanbo Li, Zakary Littlefield, Kostas E. Bekris
Sampling-based algorithms are viewed as practical solutions for high-dimensional motion planning. Recent progress has taken advantage of random geometric graph theory to show how a…