74 citations · 82 across the 6 of their papers we have counts for
12 papers
Cost Splitting for Multi-Objective Conflict-Based Search
Cheng Ge, Han Zhang, Jiaoyang Li +1
The Multi-Objective Multi-Agent Path Finding (MO-MAPF) problem is the problem of finding the Pareto-optimal frontier of collision-free paths for a team of agents while minimizing m…
A MIP-Based Approach for Multi-Robot Geometric Task-and-Motion Planning
Hejia Zhang, Shao-Hung Chan, Jie Zhong +3
We address multi-robot geometric task-and-motion planning (MR-GTAMP) problems in synchronous, monotone setups. The goal of the MR-GTAMP problem is to move objects with multiple rob…
Symmetry Breaking for k-Robust Multi-Agent Path Finding
Zhe Chen, Daniel Harabor, Jiaoyang Li +1
During Multi-Agent Path Finding (MAPF) problems, agents can be delayed by unexpected events. To address such situations recent work describes k-Robust Conflict-BasedSearch (k-CBS):…
Scalable and Safe Multi-Agent Motion Planning with Nonlinear Dynamics and Bounded Disturbances
Jingkai Chen, Jiaoyang Li, Chuchu Fan +1
We present a scalable and effective multi-agent safe motion planner that enables a group of agents to move to their desired locations while avoiding collisions with obstacles and o…
EECBS: A Bounded-Suboptimal Search for Multi-Agent Path Finding
Jiaoyang Li, Wheeler Ruml, Sven Koenig
Multi-Agent Path Finding (MAPF), i.e., finding collision-free paths for multiple robots, is important for many applications where small runtimes are necessary, including the kind o…
Integer Programming for Multi-Robot Planning: A Column Generation Approach
Naveed Haghani, Jiaoyang Li, Sven Koenig +3
We consider the problem of coordinating a fleet of robots in a warehouse so as to maximize the reward achieved within a time limit while respecting problem and robot specific const…