activity
20222024
most citedArbitrarily Scalable Environment Generators via Neural Cellular Automata

5 citations · 12 across the 12 of their papers we have counts for

collaborators

14 papers

cs.MA2024

From Space-Time to Space-Order: Directly Planning a Temporal Planning Graph by Redefining CBS

Yu Wu, Rishi Veerapaneni, Jiaoyang Li +1

The majority of multi-agent path finding (MAPF) methods compute collision-free space-time paths which require agents to be at a specific location at a specific discretized timestep…

cs.AI20241 cited

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…

cs.RO2024

Caching-Augmented Lifelong Multi-Agent Path Finding

Yimin Tang, Zhenghong Yu, Yi Zheng +3

Multi-Agent Path Finding (MAPF), which involves finding collision-free paths for multiple robots, is crucial in various applications. Lifelong MAPF, where targets are reassigned to…

cs.MA2024

No Panacea in Planning: Algorithm Selection for Suboptimal Multi-Agent Path Finding

Weizhe Chen, Zhihan Wang, Jiaoyang Li +2

Since more and more algorithms are proposed for multi-agent path finding (MAPF) and each of them has its strengths, choosing the correct one for a specific scenario that fulfills s…

cs.RO20241 cited

Accelerating Search-Based Planning for Multi-Robot Manipulation by Leveraging Online-Generated Experiences

Yorai Shaoul, Itamar Mishani, Maxim Likhachev +1

An exciting frontier in robotic manipulation is the use of multiple arms at once. However, planning concurrent motions is a challenging task using current methods. The high-dimensi…

cs.MA20241 cited

Improving Learnt Local MAPF Policies with Heuristic Search

Rishi Veerapaneni, Qian Wang, Kevin Ren +3

Multi-agent path finding (MAPF) is the problem of finding collision-free paths for a team of agents to reach their goal locations. State-of-the-art classical MAPF solvers typically…