Cooperative control of mobile sensor networks:Adaptive gradient climbing in a distributed environment

We present a stable control strategy for groups of vehicles to move and reconfigure cooperatively in response to a sensed, distributed environment. Each vehicle in the group serves as a mobile sensor and the vehicle network as a mobile and reconfigurable sensor array. Our control strategy decouples, in part, the cooperative management of the network formation from the network maneuvers. The underlying coordination framework uses virtual bodies and artificial potentials. We focus on gradient climbing missions in which the mobile sensor network seeks out local maxima or minima in the environmental field. The network can adapt its configuration in response to the sensed environment in order to optimize its gradient climb.

[1]  Petter Ögren,et al.  Formations with a Mission: Stable Coordination of Vehicle Group Maneuvers , 2002 .

[2]  Naomi Ehrich Leonard,et al.  Virtual leaders, artificial potentials and coordinated control of groups , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[3]  A. Ōkubo Dynamical aspects of animal grouping: swarms, schools, flocks, and herds. , 1986, Advances in biophysics.

[4]  Richard A. Davis,et al.  Time Series: Theory and Methods (2nd ed.). , 1992 .

[5]  K.M. Passino,et al.  Stability analysis of social foraging swarms , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[6]  Randal W. Beard,et al.  A decentralized approach to formation maneuvers , 2003, IEEE Trans. Robotics Autom..

[7]  A. Mogilner,et al.  Mathematical Biology Mutual Interactions, Potentials, and Individual Distance in a Social Aggregation , 2003 .

[8]  L. Edelstein-Keshet,et al.  Complexity, pattern, and evolutionary trade-offs in animal aggregation. , 1999, Science.

[9]  Craig W. Reynolds Flocks, herds, and schools: a distributed behavioral model , 1987, SIGGRAPH.

[10]  Francesco Bullo,et al.  COVERAGE CONTROL FOR MOBILE SENSING NETWORKS: VARIATIONS ON A THEME , 2002 .

[11]  Douglas A. Hoskins,et al.  Least action approach to collective behavior , 1995, Other Conferences.

[12]  D. Grünbaum Schooling as a strategy for taxis in a noisy environment , 1998, Evolutionary Ecology.

[13]  Philip Rabinowitz,et al.  Methods of Numerical Integration , 1985 .

[14]  Yang Liu,et al.  Stability analysis of one-dimensional asynchronous swarms , 2003, IEEE Trans. Autom. Control..

[15]  Julia K. Parrish,et al.  Animal Groups in Three Dimensions: Analysis , 1997 .

[16]  K.M. Passino,et al.  Stability analysis of social foraging swarms: combined effects of attractant/repellent profiles , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[17]  Richard A. Davis,et al.  Time Series: Theory and Methods , 2013 .

[18]  Richard M. Murray,et al.  DISTRIBUTED COOPERATIVE CONTROL OF MULTIPLE VEHICLE FORMATIONS USING STRUCTURAL POTENTIAL FUNCTIONS , 2002 .

[19]  I. Rhodes A tutorial introduction to estimation and filtering , 1971 .

[20]  Daniel E. Koditschek,et al.  Exact robot navigation using artificial potential functions , 1992, IEEE Trans. Robotics Autom..

[21]  Kevin Barraclough,et al.  I and i , 2001, BMJ : British Medical Journal.

[22]  Randal W. Beard,et al.  A control scheme for improving multi-vehicle formation maneuvers , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[23]  H. Berg Random Walks in Biology , 2018 .

[24]  J. Bellingham,et al.  Autonomous Oceanographic Sampling Networks , 1993 .

[25]  Andrea L. Bertozzi,et al.  Tracking Environmental Level Sets with Autonomous Vehicles , 2004 .

[26]  Naomi Ehrich Leonard,et al.  Adaptive Sampling Using Feedback Control of an Autonomous Underwater Glider Fleet , 2003 .

[27]  Petter Ögren,et al.  A control Lyapunov function approach to multi-agent coordination , 2001 .

[28]  Xiaoming Hu,et al.  A control Lyapunov function approach to multiagent coordination , 2002, IEEE Trans. Robotics Autom..

[29]  George J. Pappas,et al.  Stable flocking of mobile agents, part I: fixed topology , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[30]  D. Yoerger,et al.  Gradient search with autonomous underwater vehicles using scalar measurements , 1996, Proceedings of Symposium on Autonomous Underwater Vehicle Technology.

[31]  Naomi Ehrich Leonard,et al.  Vehicle networks for gradient descent in a sampled environment , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[32]  Stan Uryasev,et al.  Derivatives of probability functions and some applications , 1995, Ann. Oper. Res..

[33]  O. Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.

[34]  Audra E. Kosh,et al.  Linear Algebra and its Applications , 1992 .