16 citations · 24 across the 21 of their papers we have counts for
22 papers
MR-SPITE: Accelerating Multi-Robot Conflict Scans via Hierarchical Swept-Volume Approximations
Marta Markowicz, James Motes, Marco Morales +1
Conflict scanning over synchronized robot paths requires detailed collision checking, potentially across every robot pair at every timestep, and may be repeated many times as confl…
AO-ARC: Almost-Surely Asymptotically Optimal Multi-Robot Motion Planning with ARC
James D. Motes, Marco Morales, Nancy M. Amato
We present AO-ARC, an anytime multi-robot motion planning (MRMP) method that achieves initial solution times on par with state-of-the-art MRMP feasibility solvers while converging…
P-ARC: Exploiting Subproblem Independence for Parallel Multi-Robot Motion Planning
James D. Motes, Marco Morales, Nancy M. Amato
This paper presents Parallel ARC (P-ARC), a parallel formulation of the Adaptive Robot Coordination (ARC) approach to multi-robot motion planning (MRMP) which exploits subproblem i…
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…
Multi-Robot Motions in Milliseconds: Vector-Accelerated Primitives for Sampling-Based Planning
James D. Motes, Marco Morales, Nancy M. Amato
In this paper, we extend the recent Vector-Accelerated Motion Planning (VAMP) framework to multi-robot motion planning. We develop two vector-accelerated primitives, multi-robot Mo…
Serialized Red-Green-Gray: Quicker Heuristic Validation of Edges in Dynamic Roadmap Graphs
Yulie Arad, Stav Ashur, Marta Markowicz +3
Motion planning in dynamic environments, such as robotic warehouses, requires fast adaptation to frequent changes in obstacle poses. Traditional roadmap-based methods struggle in s…
An Analysis of Constraint-Based Multi-Agent Pathfinding Algorithms
Hannah Lee, James D. Motes, Marco Morales +1
This study informs the design of future multi-agent pathfinding (MAPF) and multi-robot motion planning (MRMP) algorithms by guiding choices based on constraint classification for c…
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…
PRISM: Complete Online Decentralized Multi-Agent Pathfinding with Rapid Information Sharing using Motion Constraints
Hannah Lee, Zachary Serlin, James Motes +3
We introduce PRISM (Pathfinding with Rapid Information Sharing using Motion Constraints), a decentralized algorithm designed to address the multi-task multi-agent pathfinding (MT-M…
Lazy-DaSH: Lazy Approach for Hypergraph-based Multi-robot Task and Motion Planning
Seongwon Lee, James Motes, Isaac Ngui +2
We introduce Lazy-DaSH, an improvement over the recent state of the art multi-robot task and motion planning method DaSH, which scales to more than double the number of robots and…
K-ARC: Adaptive Robot Coordination for Multi-Robot Kinodynamic Planning
Mike Qin, Irving Solis, James Motes +2
This work presents Kinodynamic Adaptive Robot Coordination (K-ARC), a novel algorithm for multi-robot kinodynamic planning. Our experimental results show the capability of K-ARC to…
Experience-based Subproblem Planning for Multi-Robot Motion Planning
Irving Solis, James Motes, Mike Qin +2
Multi-robot systems enhance efficiency and productivity across various applications, from manufacturing to surveillance. While single-robot motion planning has improved by using da…
Encoding Reusable Multi-Robot Planning Strategies as Abstract Hypergraphs
Khen Elimelech, James Motes, Marco Morales +3
Multi-Robot Task Planning (MR-TP) is the search for a discrete-action plan a team of robots should take to complete a task. The complexity of such problems scales exponentially wit…
SPITE: Simple Polyhedral Intersection Techniques for modified Environments
Stav Ashur, Maria Lusardi, Marta Markowicz +4
Motion planning in modified environments is a challenging task, as it compounds the innate difficulty of the motion planning problem with a changing environment. This renders some…
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…
Adaptive Robot Coordination: A Subproblem-based Approach for Hybrid Multi-Robot Motion Planning
Irving Solis, James Motes, Mike Qin +2
This work presents Adaptive Robot Coordination (ARC), a novel hybrid framework for multi-robot motion planning (MRMP) that employs local subproblems to resolve inter-robot conflict…
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…
Hypergraph-based Multi-Robot Task and Motion Planning
James Motes, Tan Chen, Timothy Bretl +2
We present a multi-robot task and motion planning method that, when applied to the rearrangement of objects by manipulators, results in solution times up to three orders of magnitu…
Insights from an Industrial Collaborative Assembly Project: Lessons in Research and Collaboration
Tan Chen, Zhe Huang, James Motes +13
Significant progress in robotics reveals new opportunities to advance manufacturing. Next-generation industrial automation will require both integration of distinct robotic technol…
Representation-Optimal Multi-Robot Motion Planning using Conflict-Based Search
Irving Solis, Read Sandström, James Motes +1
Multi-Agent Motion Planning (MAMP) is the problem of computing feasible paths for a set of agents given individual start and goal states. Given the hardness of MAMP, most of the re…