Multi-robot systems are essential for environmental monitoring, particularly for tracking spatial phenomena like pollution, soil minerals, and water salinity, and more. This study addresses the challenge of deploying a multi-robot team for optimal coverage in environments where the density distribution, describing areas of interest, is unknown and changes over time. We propose a fully distributed control strategy that uses Gaussian Processes (GPs) to model the spatial field and balance the trade-off between learning the field and optimally covering it. Unlike existing approaches, we address a more realistic scenario by handling time-varying spatial fields, where the exploration-exploitation trade-off is dynamically adjusted over time. Each robot operates locally, using only its own collected data and the information shared by the neighboring robots. To address the computational limits of GPs, the algorithm efficiently manages the volume of data by selecting only the most relevant samples for the process estimation. The performance of the proposed algorithm is evaluated through several simulations and experiments, incorporating real-world data phenomena to validate its effectiveness.
D2CoPlan: A Differentiable Decentralized Planner for Multi-Robot Coverage
University of Maryland, College Park（马里兰大学帕克分校）；Drexel University（德雷塞尔大学）
多机器人覆盖规划问题的集中式方法缺乏可扩展性。基于学习的分布式算法提供了一个可扩展的途径，除了将面向数据的特征生成功能带到表中，允许与其他基于学习的方法集成。为此，我们提出了一个基于学习的，可区分的分布式覆盖规划（D2COPL A N），它的规模有效地在运行时和代理的数量相比，专家算法，并执行与经典的分布式算法。此外，我们还表明，D2COPlan可以与其他学习方法无缝结合，进行端到端的学习，从而获得比单独训练的模块更好的解决方案，为进一步研究经典方法仍然难以实现的任务打开了大门。
Coverage Path Planning for Autonomous Sailboats in Inhomogeneous and Time-Varying Oceans: A Spatiotemporal Optimization Approach
Institute of Deep-sea Science and Engineering, Chinese Academy of Sciences（中国科学院深海科学与工程研究所）；Institute for Ocean Engineering, Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院海洋工程研究所）；ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University（浙江大学 Hangzhou 全球科技创新中心）；Department of Engineering, Faculty of Computing, Engineering and the Built Environment, Birmingham City University（伯明翰城市大学工程系）；School of Ocean and Civil Engineering, Shanghai Jiao Tong University（上海交通大学海洋与Civil Engineering学院）
Loss of Distributed Coverage Using Lazy Agents Operating Under Discrete, Local, Event-Triggered Communication
SHL（SHL公司）；TCS Research, Tata Consultancy Services Ltd.（塔塔咨询服务有限公司TCS研究院）；Imperial College London（帝国理工学院）；Indian Institute of Technology Bombay（印度理工学院孟买分校）
Distributed Coverage Control of Constrained Constant-Speed Unicycle Multi-Agent Systems
University of Science and Technology of China（中国科学技术大学）；Eindhoven University of Technology（埃因霍温理工大学）；Technical University of Munich（慕尼黑工业大学）；Ningbo Institute of Intelligent Equipment Technology Company Ltd（宁波智能装备技术研究院有限公司）
