16 citations · 18 across the 7 of their papers we have counts for
7 papers · 1 filter
Scalable Multi-robot Motion Planning via Hierarchical Subproblem Expansion and Workspace Decomposition Refinement
Isaac Ngui, Courtney McBeth, James D. Motes +2
A fundamental challenge in multi-robot motion planning is achieving sufficient coordination to avoid inter-robot conflicts without incurring the large computational expense of sear…
ERUPT: An Open Toolkit for Interfacing with Robot Motion Planners in Extended Reality
Isaac Ngui, Courtney McBeth, André Santos +6
We present the Extended Reality Universal Planning Toolkit (ERUPT), an extended reality (XR) system for interactive motion planning. This paper serves to introduce our open-source…
Extended Reality System for Robotic Learning from Human Demonstration
Isaac Ngui, Courtney McBeth, Grace He +4
Many real-world tasks are intuitive for a human to perform, but difficult to encode algorithmically when utilizing a robot to perform the tasks. In these scenarios, robotic systems…
A Framework for Guided Motion Planning
Amnon Attali, Stav Ashur, Isaac Burton Love +4
Randomized sampling based algorithms are widely used in robot motion planning due to the problem's intractability, and are experimentally effective on a wide range of problem insta…
Scalable Multi-Robot Motion Planning Using Workspace Guidance-Informed Hypergraphs
Courtney McBeth, James Motes, Isaac Ngui +2
In this work, we propose a method for multiple mobile robot motion planning that efficiently plans for robot teams up to 128 robots (an order of magnitude larger than existing stat…
Evaluating Guiding Spaces for Motion Planning
Amnon Attali, Stav Ashur, Isaac Burton Love +5
Randomized sampling based algorithms are widely used in robot motion planning due to the problem's intractability, and are experimentally effective on a wide range of problem insta…
Scalable Multi-robot Motion Planning for Congested Environments With Topological Guidance
Courtney McBeth, James Motes, Diane Uwacu +2
Multi-robot motion planning (MRMP) is the problem of finding collision-free paths for a set of robots in a continuous state space. The difficulty of MRMP increases with the number…