In this paper, we design an information-based multi-robot source seeking algorithm where a group of mobile sensors localizes and moves close to a single source using only local range-based measurements. In the algorithm, the mobile sensors perform source identification/localization to estimate the source location; meanwhile, they move to new locations to maximize the Fisher information about the source contained in the sensor measurements. In doing so, they improve the source location estimate and move closer to the source. Our algorithm is superior in convergence speed compared with traditional field climbing algorithms, is flexible in the measurement model and the choice of information metric, and is robust to measurement model errors. Moreover, we provide a fully distributed version of our algorithm, where each sensor decides its own actions and only shares information with its neighbors through a sparse communication network. We perform intensive simulation experiments to test our algorithms on large-scale systems and physical experiments on small ground vehicles with light sensors, demonstrating success in seeking a light source.
Distributed Multi-robot Source Seeking in Unknown Environments with Unknown Number of Sources
Robotics Institute at Carnegie Mellon University（卡内基梅隆大学 机器人研究所）；School of Interactive Computing at Georgia Institute of Technology（佐治亚理工学院 交互计算学院）；University of Illinois Chicago（芝加哥大学伊利诺伊分校）
针对源数量未知且可能多于机器人数量的多机器人搜寻问题，提出分布式 DIAS 框架，通过混合探索/利用控制、Voronoi 分区与高斯过程回归提升源识别和密度估计性能。
BEASST: Behavioral Entropic Gradient based Adaptive Source Seeking for Mobile Robots
Department of Mechanical and Aerospace Engineering, University of California, Irvine（加州大学尔湾分校机械与航空航天工程系）；U.S. DEVCOM Army Research Laboratory (ARL)（美国陆军研究实验室）
Acceleration based PSO for Multi-UAV Source-Seeking
Robotics Research Center, International Institute of Information Technology（国际信息技术学院机器人研究中心）；Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR)（新加坡科技研究局（A*STAR）信息通信研究院）；International Institute of Information Technology（国际信息技术学院）；Institute for Infocomm Research（信息通信研究院）；Agency for Science, Technology and Research (A*STAR)（新加坡科技研究局（A*STAR））
Model-Free and Real-Time Unicycle-Based Source Seeking with Differential Wheeled Robotic Experiments
PhD Student, Department of Aerospace Engineering（航空航天工程系博士研究生）；Engineering Mechanics, University of Cincinnati, OH, USA（辛辛那提大学工程力学系）；Assistant Professor, Department of Aerospace Engineering（航空航天工程系助理教授）；MS Student, Department of Aerospace Engineering（航空航天工程系硕士研究生）
Model-free source seeking of exponentially convergent unicycle: theoretical and robotic experimental results
Department of Aerospace Engineering and Engineering Mechanics（航空航天工程与工程力学系）；University of Cincinnati（辛辛那提大学）；Department of Mathematics（数学系）；University of Klagenfurt（克雷格弗特大学）
