1 citations · 1 across the 11 of their papers we have counts for
11 papers
Planner-Conditioned Diffusion for Coordinated Multi-Agent Exploration
Marcus Yu Siong Teo, Jeric Lew, Tanishq Duhan +1
Coordinated multi-agent exploration requires not only efficient individual coverage but also non-redundant coverage across agents over extended planning horizons. Conventional appr…
Search-Aided Joint Agent-Environment Reinforcement Learning for Robust Lifelong Multi-Agent Path Finding with Rotations
He Jiang, Jingtian Yan, Yulun Zhang +5
Lifelong Multi-Agent Path Finding (LMAPF) requires repeatedly planning collision-free paths for agents that continuously receive new goals upon reaching their current ones. While m…
PRIMAL3: Pathfinding via Reinforcement and Imitation Multi-Agent Learning - Leveraging LaCAM3
Chengyang He, Tanishq Duhan, Gadiel Sznaier Camps +6
We present PRIMAL3, an ultra-large-scale learning-based framework for multi-agent pathfinding (MAPF) that integrates reinforcement learning, topology-aware communication, LaCAM3-gu…
COIN: Collaborative Interaction-Aware Multi-Agent Reinforcement Learning for Self-Driving Systems
Yifeng Zhang, Jieming Chen, Tingguang Zhou +4
Multi-Agent Self-Driving (MASD) systems provide an effective solution for coordinating autonomous vehicles to reduce congestion and enhance both safety and operational efficiency i…
CAMO: A Conditional Neural Solver for the Multi-objective Multiple Traveling Salesman Problem
Fengxiaoxiao Li, Xiao Mao, Mingfeng Fan +4
Robotic systems often require a team of robots to collectively visit multiple targets while optimizing competing objectives, such as total travel cost and makespan. This setting ca…
HMR-ODTA: Online Diverse Task Allocation for a Team of Heterogeneous Mobile Robots
Ashish Verma, Avinash Gautam, Tanishq Duhan +2
Coordinating time-sensitive deliveries in environments like hospitals poses a complex challenge, particularly when managing multiple online pickup and delivery requests within stri…
Search-TTA: A Multimodal Test-Time Adaptation Framework for Visual Search in the Wild
Derek Ming Siang Tan, Shailesh, Boyang Liu +8
To perform outdoor visual navigation and search, a robot may leverage satellite imagery to generate visual priors. This can help inform high-level search strategies, even when such…
Deploying Ten Thousand Robots: Scalable Imitation Learning for Lifelong Multi-Agent Path Finding
He Jiang, Yutong Wang, Rishi Veerapaneni +3
Lifelong Multi-Agent Path Finding (LMAPF) repeatedly finds collision-free paths for multiple agents that are continually assigned new goals when they reach current ones. Recently,…
Social Behavior as a Key to Learning-based Multi-Agent Pathfinding Dilemmas
Chengyang He, Tanishq Duhan, Parth Tulsyan +2
The Multi-agent Path Finding (MAPF) problem involves finding collision-free paths for a team of agents in a known, static environment, with important applications in warehouse auto…
LNS2+RL: Combining Multi-Agent Reinforcement Learning with Large Neighborhood Search in Multi-Agent Path Finding
Yutong Wang, Tanishq Duhan, Jiaoyang Li +1
Multi-Agent Path Finding (MAPF) is a critical component of logistics and warehouse management, which focuses on planning collision-free paths for a team of robots in a known enviro…
ALPHA: Attention-based Long-horizon Pathfinding in Highly-structured Areas
Chengyang He, Tianze Yang, Tanishq Duhan +2
The multi-agent pathfinding (MAPF) problem seeks collision-free paths for a team of agents from their current positions to their pre-set goals in a known environment, and is an ess…