6 papers
A Generalized Voronoi Graph based Coverage Control Approach for Non-Convex Environment
Zuyi Guo, Ronghao Zheng, Meiqin Liu +1
To address the challenge of efficient coverage by multi-robot systems in non-convex regions with multiple obstacles, this paper proposes a coverage control method based on the Gene…
Balanced Collaborative Exploration via Distributed Topological Graph Voronoi Partition
Tianyi Ding, Ronghao Zheng, Senlin Zhang +1
This work addresses the collaborative multi-robot autonomous online exploration problem, particularly focusing on distributed exploration planning for dynamically balanced explorat…
GAWM: Global-Aware World Model for Multi-Agent Reinforcement Learning
Zifeng Shi, Meiqin Liu, Senlin Zhang +3
In recent years, Model-based Multi-Agent Reinforcement Learning (MARL) has demonstrated significant advantages over model-free methods in terms of sample efficiency by using indepe…
RMIO: A Model-Based MARL Framework for Scenarios with Observation Loss in Some Agents
Zifeng Shi, Meiqin Liu, Senlin Zhang +2
In recent years, model-based reinforcement learning (MBRL) has emerged as a solution to address sample complexity in multi-agent reinforcement learning (MARL) by modeling agent-env…
Relation DETR: Exploring Explicit Position Relation Prior for Object Detection
Xiuquan Hou, Meiqin Liu, Senlin Zhang +3
This paper presents a general scheme for enhancing the convergence and performance of DETR (DEtection TRansformer). We investigate the slow convergence problem in transformers from…
Cooperative Reward Shaping for Multi-Agent Pathfinding
Zhenyu Song, Ronghao Zheng, Senlin Zhang +1
The primary objective of Multi-Agent Pathfinding (MAPF) is to plan efficient and conflict-free paths for all agents. Traditional multi-agent path planning algorithms struggle to ac…