18 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…
Path Database Guidance for Motion Planning
Amnon Attali, Praval Telagi, Marco Morales +1
One approach to using prior experience in robot motion planning is to store solutions to previously seen problems in a database of paths. Methods that use such databases are charac…
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…
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…
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…