Decentralized, Adaptive Coverage Control for Networked Robots
International Journal of Robotics Research
Distributed sampling of random fields with unknown covariance
ACC'09 Proceedings of the 2009 conference on American Control Conference
Decentralized H∞ filtering in a multi-agent system
ACC'09 Proceedings of the 2009 conference on American Control Conference
Toward model free atmospheric sensing by aerial robot networks in strong wind fields
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Brief paper: Decentralized estimation and control of graph connectivity for mobile sensor networks
Automatica (Journal of IFAC)
Particle filter based information-theoretic active sensing
Robotics and Autonomous Systems
Dynamic average consensus via nonlinear protocols
Automatica (Journal of IFAC)
Distributed robotic sensor networks: An information-theoretic approach
International Journal of Robotics Research
Journal of Intelligent and Robotic Systems
Automatica (Journal of IFAC)
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Cooperating mobile sensors can be used to model environmental functions such as the temperature or salinity of a region of ocean. In this paper, we adopt an optimal filtering approach to fusing local sensor data into a global model of the environment. Our approach is based on the use of proportional-integral (PI) average consensus estimators, whereby information from each mobile sensor diffuses through the communication network. As a result, this approach is scalable and fully decentralized, and allows changing network topologies and anonymous agents to be added and subtracted at any time. We also derive control laws for mobile sensors to move to maximize their sensory information relative to current uncertainties in the model. The approach is demonstrated by simulations including modeling ocean temperature.