1 citations · 3 across the 10 of their papers we have counts for
11 papers
ITA-LaCAM: A Complete and Scalable TAPF Solver via Assignment-Aware Configuration-Space Search
Yimin Tang, Han Zhang, Shao-Hung Chan +4
Combined Target Assignment and Path Finding (TAPF) requires assigning targets for agents while simultaneously planning collision-free paths. We present ITA-LaCAM, a complete and sc…
Conflict Mitigation in Shared Environments using Flow-Aware Multi-Agent Path Finding
Lukas Heuer, Yufei Zhu, Luigi Palmieri +4
Deploying multi-robot systems in environments shared with dynamic and uncontrollable agents presents significant challenges, especially for large robot fleets. In such environments…
Judgelight: Trajectory-Level Post-Optimization for Multi-Agent Path Finding via Closed-Subwalk Collapsing
Yimin Tang, Sven Koenig, Erdem Bıyık
Multi-Agent Path Finding (MAPF) is an NP-hard problem with applications in warehouse automation and multi-robot coordination. Learning-based MAPF solvers offer fast and scalable pl…
New Mechanisms in Flex Distribution for Bounded Suboptimal Multi-Agent Path Finding
Shao-Hung Chan, Thomy Phan, Jiaoyang Li +1
Multi-Agent Path Finding (MAPF) is the problem of finding a set of collision-free paths, one for each agent in a shared environment. Its objective is to minimize the sum of path co…
Accelerating Focal Search in Multi-Agent Path Finding with Tighter Lower Bounds
Yimin Tang, Zhenghong Yu, Jiaoyang Li +1
Multi-Agent Path Finding (MAPF) involves finding collision-free paths for multiple agents while minimizing a cost function--an NP-hard problem. Bounded suboptimal methods like Enha…
RAILGUN: A Unified Convolutional Policy for Multi-Agent Path Finding Across Different Environments and Tasks
Yimin Tang, Xiao Xiong, Jingyi Xi +3
Multi-Agent Path Finding (MAPF), which focuses on finding collision-free paths for multiple robots, is crucial for applications ranging from aerial swarms to warehouse automation.…
Enhancing Lifelong Multi-Agent Path Finding with Cache Mechanism
Yimin Tang, Zhenghong Yu, Yi Zheng +3
Multi-Agent Path Finding (MAPF), which focuses on finding collision-free paths for multiple robots, is crucial in autonomous warehouse operations. Lifelong MAPF (L-MAPF), where age…
Anytime Multi-Agent Path Finding with an Adaptive Delay-Based Heuristic
Thomy Phan, Benran Zhang, Shao-Hung Chan +1
Anytime multi-agent path finding (MAPF) is a promising approach to scalable path optimization in multi-agent systems. MAPF-LNS, based on Large Neighborhood Search (LNS), is the cur…
ITA-ECBS: A Bounded-Suboptimal Algorithm for the Combined Target-Assignment and Path-Finding Problem
Yimin Tang, Sven Koenig, Jiaoyang Li
Multi-Agent Path Finding (MAPF), i.e., finding collision-free paths for multiple robots, plays a critical role in many applications. Sometimes, assigning a target to each agent als…
Anytime Multi-Agent Path Finding using Operation Parallelism in Large Neighborhood Search
Shao-Hung Chan, Zhe Chen, Dian-Lun Lin +5
Multi-Agent Path Finding (MAPF) is the problem of finding a set of collision-free paths for multiple agents in a shared environment while minimizing the sum of travel time. Since s…
Multi-Robot Geometric Task-and-Motion Planning for Collaborative Manipulation Tasks
Hejia Zhang, Shao-Hung Chan, Jie Zhong +6
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…