3 citations · 7 across the 3 of their papers we have counts for
5 papers
MUI-TARE: Multi-Agent Cooperative Exploration with Unknown Initial Position
Jingtian Yan, Xingqiao Lin, Zhongqiang Ren +6
Multi-agent exploration of a bounded 3D environment with unknown initial positions of agents is a challenging problem. It requires quickly exploring the environments as well as rob…
Enhanced Multi-Objective A* Using Balanced Binary Search Trees
Zhongqiang Ren, Richard Zhan, Sivakumar Rathinam +2
This work addresses a Multi-Objective Shortest Path Problem (MO-SPP) on a graph where the goal is to find a set of Pareto-optimal solutions from a start node to a destination in th…
Subdimensional Expansion Using Attention-Based Learning For Multi-Agent Path Finding
Lakshay Virmani, Zhongqiang Ren, Sivakumar Rathinam +1
Multi-Agent Path Finding (MAPF) finds conflict-free paths for multiple agents from their respective start to goal locations. MAPF is challenging as the joint configuration space gr…
MS*: A New Exact Algorithm for Multi-agent Simultaneous Multi-goal Sequencing and Path Finding
Zhongqiang Ren, Sivakumar Rathinam, Howie Choset
In multi-agent applications such as surveillance and logistics, fleets of mobile agents are often expected to coordinate and safely visit a large number of goal locations as effici…
Subdimensional Expansion for Multi-objective Multi-agent Path Finding
Zhongqiang Ren, Sivakumar Rathinam, Howie Choset
Conventional multi-agent path planners typically determine a path that optimizes a single objective, such as path length. Many applications, however, may require multiple objective…