14 citations · 16 across the 11 of their papers we have counts for
11 papers
Goal Staying Makes Sum-of-Costs Anonymous Multi-Agent Path Finding NP-Hard
Hang Ma
Anonymous Multi-Agent Path Finding (AMAPF) admits polynomial-time network-flow algorithms for several objectives, including makespan, total distance, and sum-of-costs (SoC) when ag…
Unified Branch-and-Bound Search for the Steiner Traveling Salesman Problem on Graphs of Convex Sets
Jingtao Tang, Hang Ma
We formalize the Steiner Traveling Salesman Problem (Steiner-TSP) on Graphs of Convex Sets (GCS), which seeks a minimum-cost closed trajectory through required convex sets while al…
Search-Based Spatiotemporal and Multi-Robot Motion Planning on Graphs of Space-Time Convex Sets
Jingtao Tang, Zining Mao, Lufan Yang +1
Spatiotemporal motion planning, especially in multi-robot settings, requires robots to reason about collision-free regions that change over time, which is challenging in continuous…
GHOST: Solving the Traveling Salesman Problem on Graphs of Convex Sets
Jingtao Tang, Hang Ma
We study GCS-TSP, a new variant of the Traveling Salesman Problem (TSP) defined over a Graph of Convex Sets (GCS) -- a powerful representation for trajectory planning that decompos…
Adaptation and Fine-tuning with TabPFN for Travelling Salesman Problem
Nguyen Gia Hien Vu, Yifan Tang, Rey Lim +4
Tabular Prior-Data Fitted Network (TabPFN) is a foundation model designed for small to medium-sized tabular data, which has attracted much attention recently. This paper investigat…
Space-Time Graphs of Convex Sets for Multi-Robot Motion Planning
Jingtao Tang, Zining Mao, Lufan Yang +1
We address the Multi-Robot Motion Planning (MRMP) problem of computing collision-free trajectories for multiple robots in shared continuous environments. While existing frameworks…
Large-Scale Multirobot Coverage Path Planning on Grids With Path Deconfliction
Jingtao Tang, Zining Mao, Hang Ma
We study Multi-Robot Coverage Path Planning (MCPP) on a 4-neighbor 2D grid G, which aims to compute paths for multiple robots to cover all cells of G. Traditional approaches are li…
MFC-EQ: Mean-Field Control with Envelope Q-Learning for Moving Decentralized Agents in Formation
Qiushi Lin, Hang Ma
We study a decentralized version of Moving Agents in Formation (MAiF), a variant of Multi-Agent Path Finding aiming to plan collision-free paths for multiple agents with the dual o…
Multi-Robot Connected Fermat Spiral Coverage
Jingtao Tang, Hang Ma
We introduce the Multi-Robot Connected Fermat Spiral (MCFS), a novel algorithmic framework for Multi-Robot Coverage Path Planning (MCPP) that adapts Connected Fermat Spiral (CFS) f…
Large-Scale Multi-Robot Coverage Path Planning via Local Search
Jingtao Tang, Hang Ma
We study graph-based Multi-Robot Coverage Path Planning (MCPP) that aims to compute coverage paths for multiple robots to cover all vertices of a given 2D grid terrain graph . E…
A Competitive Analysis of Online Multi-Agent Path Finding
Hang Ma
We study online Multi-Agent Path Finding (MAPF), where new agents are constantly revealed over time and all agents must find collision-free paths to their given goal locations. We…