Deployment algorithms for a power-constrained mobile sensor network

This paper presents coverage algorithms for mobile sensor networks in which agents have limited power to move. Rather than making use of a constrained optimization technique, our approach accounts for power constraints by assigning non-homogeneously time-varying regions to each robot. This leads to a novel partition of the environment into limited-range, generalized Voronoi regions. The motion control algorithms are then designed to ascend the gradient of several types of locational optimization functions. In particular, the objective functions reflect the global energy available to the group and different coverage criteria. As we discuss in the paper, this has an effect on limiting each agent's velocity to save energy and balance its expenditure across the network.

[1]  Mani B. Srivastava,et al.  Energy-aware wireless systems with adaptive power-fidelity tradeoffs , 2005, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[2]  Gaurav S. Sukhatme,et al.  Mobile Sensor Network Deployment using Potential Fields : A Distributed , Scalable Solution to the Area Coverage Problem , 2002 .

[3]  Sonia Martínez,et al.  Coverage control for mobile sensing networks , 2002, IEEE Transactions on Robotics and Automation.

[4]  Gaurav S. Sukhatme,et al.  Connecting the Physical World with Pervasive Networks , 2002, IEEE Pervasive Comput..

[5]  Francesco Bullo,et al.  Esaim: Control, Optimisation and Calculus of Variations Spatially-distributed Coverage Optimization and Control with Limited-range Interactions , 2022 .

[6]  S. P. Lloyd,et al.  Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.

[7]  Jorge Cortés,et al.  Finite-time convergent gradient flows with applications to network consensus , 2006, Autom..

[8]  Y. Charlie Hu,et al.  Determining the fleet size of mobile robots with energy constraints , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[9]  Nikil D. Dutt,et al.  DYNAMO: A Cross-Layer Framework for End-to-End QoS and Energy Optimization in Mobile Handheld Devices , 2007, IEEE Journal on Selected Areas in Communications.

[10]  Y. Charlie Hu,et al.  Deployment of mobile robots with energy and timing constraints , 2006, IEEE Transactions on Robotics.

[11]  Calin Belta,et al.  Abstraction and control for Groups of robots , 2004, IEEE Transactions on Robotics.

[12]  Thomas F. La Porta,et al.  Movement-assisted sensor deployment , 2004, IEEE INFOCOM 2004.

[13]  Mac Schwager,et al.  Distributed Coverage Control with Sensory Feedback for Networked Robots , 2006, Robotics: Science and Systems.

[14]  Sonia Martínez,et al.  Energy-balancing cooperative strategies for sensor deployment , 2007, 2007 46th IEEE Conference on Decision and Control.

[15]  Gaurav S. Sukhatme,et al.  Constrained coverage for mobile sensor networks , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[16]  Pramod K. Varshney,et al.  Energy-efficient deployment of Intelligent Mobile sensor networks , 2005, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.