20 citations · 28 across the 12 of their papers we have counts for
3 papers · 1 filter
Scaling Long-Horizon Online POMDP Planning via Rapid State Space Sampling
Yuanchu Liang, Edward Kim, Wil Thomason +3
Partially Observable Markov Decision Processes (POMDPs) are a general and principled framework for motion planning under uncertainty. Despite tremendous improvement in the scalabil…
Nearest-Neighbourless Asymptotically Optimal Motion Planning with Fully Connected Informed Trees (FCIT*)
Tyler S. Wilson, Wil Thomason, Zachary Kingston +2
Improving the performance of motion planning algorithms for high-degree-of-freedom robots usually requires reducing the cost or frequency of computationally expensive operations. T…
Collision-Affording Point Trees: SIMD-Amenable Nearest Neighbors for Fast Collision Checking
Clayton W. Ramsey, Zachary Kingston, Wil Thomason +1
Motion planning against sensor data is often a critical bottleneck in real-time robot control. For sampling-based motion planners, which are effective for high-dimensional systems…