58 citations · 276 across the 26 of their papers we have counts for
3 papers · 2 filters
An Asymptotically-Optimal Sampling-Based Algorithm for Bi-directional Motion Planning
Joseph A. Starek, Javier V. Gomez, Edward Schmerling +3
Bi-directional search is a widely used strategy to increase the success and convergence rates of sampling-based motion planning algorithms. Yet, few results are available that merg…
Monte Carlo Motion Planning for Robot Trajectory Optimization Under Uncertainty
Lucas Janson, Edward Schmerling, Marco Pavone
This article presents a novel approach, named MCMP (Monte Carlo Motion Planning), to the problem of motion planning under uncertainty, i.e., to the problem of computing a low-cost…
Deterministic Sampling-Based Motion Planning: Optimality, Complexity, and Performance
Lucas Janson, Brian Ichter, Marco Pavone
Probabilistic sampling-based algorithms, such as the probabilistic roadmap (PRM) and the rapidly-exploring random tree (RRT) algorithms, represent one of the most successful approa…