1 citations · 2 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
Stochastic Implicit Neural Signed Distance Functions for Safe Motion Planning under Sensing Uncertainty
Carlos Quintero-Peña, Wil Thomason, Zachary Kingston +2
Motion planning under sensing uncertainty is critical for robots in unstructured environments to guarantee safety for both the robot and any nearby humans. Most work on planning un…
Motions in Microseconds via Vectorized Sampling-Based Planning
Wil Thomason, Zachary Kingston, Lydia E. Kavraki
Modern sampling-based motion planning algorithms typically take between hundreds of milliseconds to dozens of seconds to find collision-free motions for high degree-of-freedom prob…
Object Reconfiguration with Simulation-Derived Feasible Actions
Yiyuan Lee, Wil Thomason, Zachary Kingston +1
3D object reconfiguration encompasses common robot manipulation tasks in which a set of objects must be moved through a series of physically feasible state changes into a desired f…