Home Page for Juan Irving Solis Vidana | Parasol Laboratory

Picture Juan Irving Solis Vidana
PhD Student
Parasol Laboratory url: http://parasollab.web.illinois.edu/~juanis/
Department of Computer Science email:
University of Illinois at Urbana-Champaign office: 3307 Siebel Center
Urbana, IL 61801, USA


Hi!, My name is Juan Irving Solis and I am a PhD visiting student from Texas A&M University. I joined the lab during Spring 2016 . My research interests are Motion Planning, particularly for Multi-robot Systems. I am currently working on developing algorithms for solving the Multi-agent Motion Planning problem (MAMP).


Representation-Optimal Multi-Robot Motion Planning using Conflict-Based Search, Irving Solis, James Motes, Read Sandström, Nancy M. Amato, IEEE Robotics and Automation Letters, Mar 2021. DOI: https://doi.org/10.1109/LRA.2021.3068910
Keywords: Industrial Applications, Motion Planning, Multi-Agent
Links : [Published] [Manuscript]


title={Representation-optimal multi-robot motion planning using conflict-based search},
author={Solis, Irving and Sandstr{\"o}m, Read and Motes, James and Amato, Nancy M},
journal={arXiv preprint arXiv:1909.13352},


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 decoupled methods which provide scalable solutions but offer no optimality guarantees. Recent work has explored hybrid approaches that leverage the advantages of both coupled and decoupled approaches in an easier discrete subproblem, Multi-Agent Pathfinding (MAPF). In this work, we adapt recent developments in hybrid MAPF to the continuous domain of MAMP. We demonstrate the scalability of our method to manage groups of up to 32 agents, demonstrate the ability to handle up to 8 high-DOF manipulators, and plan for heterogeneous teams. In all scenarios, our approach plans significantly faster while providing higher quality solutions.