20 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…
From Legible to Inscrutable Trajectories: (Il)legible Motion Planning Accounting for Multiple Observers
Ananya Yammanuru, Maria Lusardi, Nancy M. Amato +1
In cooperative environments, such as in factories or assistive scenarios, it is important for a robot to communicate its intentions to observers, who could be either other humans o…
Quick Heuristic Validation of Edges in Dynamic Roadmap Graphs
Yulie Arad, Stav Ashur, Nancy M. Amato
In this paper we tackle the problem of adjusting roadmap graphs for robot motion planning to non-static environments. We introduce the "Red-Green-Gray" paradigm, a modification of…
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…
Edge Nearest Neighbor in Sampling-Based Motion Planning
Stav Ashur, Nancy M. Amato, Sariel Har-Peled
Neighborhood finders and nearest neighbor queries are fundamental parts of sampling based motion planning algorithms. Using different distance metrics or otherwise changing the def…
Faster Motion Planning via Restarts
Nancy Amato, Stav Ashur, Sariel Har-Peled%
Randomized methods such as PRM and RRT are widely used in motion planning. However, in some cases, their running-time suffers from inherent instability, leading to ``catastrophic''…
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…
Reversing the Computing Research Workforce Shortfall: Bolstering Domestic Student Pathways to PhDs
Susanne Hambrusch, Lori Pollock, Mary Hall +1
To sustain innovation and safeguard national security, the U.S. must strengthen domestic pathways to computing PhDs by engaging talented undergraduates early - before they are comm…
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…