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James Motes

10 accepted papers

2026

K-ARC: Adaptive Robot Coordination for Multi-Robot Kinodynamic Planning

ICRA 2026poster

This work presents Kinodynamic Adaptive Robot Coordination (K-ARC), a novel algorithm for multi-robot kino- dynamic planning. Our experimental results show the capability of K-ARC to plan for up to 32 planar mobile robots, while achieving up to an order of magnitude of speed-up compared to previous …

2026

Scalable Multi-Robot Motion Planning Using Workspace Guidance-Informed Hypergraphs

RA-L 2026

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 state-of-the-art methods) in congested settings with narrow passages in the environment. We achieve this improvement in scal

Cited by 0SourceScholar
2024

Adaptive Robot Coordination: A Subproblem-Based Approach for Hybrid Multi-Robot Motion Planning

RA-L 2024

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 conflicts. ARC creates subproblems centered around conflicts, and the solutions represent the robot motions required to resolve

Cited by 9SourceScholar
2023

Scalable Multi-Robot Motion Planning for Congested Environments With Topological Guidance

RA-L 2023

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 of robots and is exacerbated in environments with narrow passages that robots must pass through, like warehouse aisles w

Cited by 13SourceScholar
2021

Parallel Hierarchical Composition Conflict-Based Search for Optimal Multi-Agent Pathfinding

RA-L 2021

In this letter, we present the following optimal multi-agent pathfinding (MAPF) algorithms: Hierarchical Composition Conflict-Based Search, Parallel Hierarchical Composition Conflict-Based Search, and Dynamic Parallel Hierarchical Composition Conflict-Based Search. MAPF is the task of finding an opt

Cited by 33SourceScholar
2021

Representation-Optimal Multi-Robot Motion Planning Using Conflict-Based Search

RA-L 2021

Multi-Agent Motion Planning (MAMP) is the problem of computing feasible paths for a set of agents each with individual start and goal states within a continuous state space. Existing approaches can be split into coupled methods which provide optimal solutions but struggle with scalability or decoupl

Cited by 59SourceScholar
2020

Multi-Robot Task and Motion Planning With Subtask Dependencies

RA-L 2020

We present a multi-robot integrated task and motion method capable of handling sequential subtask dependencies within multiply decomposable tasks. We map the multi-robot pathfinding method, Conflict Based Search, to task planning and integrate this with motion planning to create TMP-CBS. TMP-CBS cou

Cited by 58SourceScholar
2019

Interaction Templates for Multi-Robot Systems

RA-L 2019

This letter describes a framework for multi-robot problems that require or utilize interactions between robots. Solutions consider interactions on a motion planning level to determine the feasibility and cost of the multi-robot team solution. Modeling these problems with current integrated task and

Cited by 12SourceScholar