Irving Solis — accepted AI-conference papers

2024

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

Irving Solis, James Motes, Mike Qin, Marco Morales, Nancy M. Amato

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 9 Source ↗Scholar ↗

2021

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

Irving Solis, James Motes, Read Sandström, Nancy M. Amato

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 59 Source ↗Scholar ↗