Multi-robot cooperative control for monitoring and tracking dynamic plumes

We study robotic tracking of dynamic plume front modeled by the advection-diffusion equation in this paper. Different from existing work purely relying on gradient measurement, the transport model of pollution source is explicitly considered in tracking control design. We first study the problem using a single robot and solve the problem in an estimation and control framework. We then extend it to the multi-robot case in a nearest-neighbor communication structure, and have the robots take formation along the plume front. The distributed control is scalable to a large number of robots. Simulation results show satisfactory performances of the proposed method.

[1]  Paolo Dario,et al.  Mapping multiple gas/odor sources in an uncontrolled indoor environment using a Bayesian occupancy grid mapping based method , 2011, Robotics Auton. Syst..

[2]  Fumin Zhang,et al.  A bio-inspired plume tracking algorithm for mobile sensing swarms in turbulent flow , 2013, 2013 IEEE International Conference on Robotics and Automation.

[3]  Yi Guo,et al.  Distributed source seeking by cooperative robots: All-to-all and limited communications , 2012, 2012 IEEE International Conference on Robotics and Automation.

[4]  Tom Duckett,et al.  Experimental analysis of smelling Braitenberg vehicles , 2003 .

[5]  Tom Duckett,et al.  Building gas concentration gridmaps with a mobile robot , 2003, Robotics Auton. Syst..

[6]  Fumin Zhang,et al.  Cooperative exploration of level surfaces of three dimensional scalar fields , 2011, Autom..

[7]  M. Arcak,et al.  Gradient climbing in formation via extremum seeking and passivity-based coordination rules , 2007, IEEE Conference on Decision and Control.

[8]  Eric Klavins,et al.  Communication Complexity of Multi-robot Systems , 2002, WAFR.

[9]  Naomi Ehrich Leonard,et al.  Exploring scalar fields using multiple sensor platforms: Tracking level curves , 2007, 2007 46th IEEE Conference on Decision and Control.

[10]  Jay A. Farrell,et al.  Plume mapping via hidden Markov methods , 2003, IEEE Trans. Syst. Man Cybern. Part B.

[11]  Jay A. Farrell,et al.  Moth-inspired chemical plume tracing on an autonomous underwater vehicle , 2006, IEEE Transactions on Robotics.

[12]  Gaurav S. Sukhatme,et al.  Planning and Implementing Trajectories for Autonomous Underwater Vehicles to Track Evolving Ocean Processes Based on Predictions from a Regional Ocean Model , 2010, Int. J. Robotics Res..

[13]  Shuo Pang,et al.  Chemical Plume Source Localization , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[14]  Thomas C. Henderson,et al.  Gradient calculation in sensor networks , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[15]  R. Fierro,et al.  Cooperative hybrid control of robotic sensors for perimeter detection and tracking , 2005, Proceedings of the 2005, American Control Conference, 2005..

[16]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.

[17]  Craig A. Woolsey,et al.  Modeling, Identification, and Control of an Unmanned Surface Vehicle , 2013, J. Field Robotics.

[18]  M. Zeitz The extended Luenberger observer for nonlinear systems , 1987 .

[19]  Jean-Daniel Boissonnat,et al.  Algorithmic Foundations of Robotics V, Selected Contributions of the Fifth International Workshop on the Algorithmic Foundations of Robotics, WAFR 2002, Nice, France, December 15-17, 2002 , 2004, WAFR.

[20]  Fumin Zhang,et al.  Adaptive control for planar curve tracking under controller uncertainty , 2013, Autom..

[21]  M. Ani Hsieh,et al.  Robotic manifold tracking of coherent structures in flows , 2012, 2012 IEEE International Conference on Robotics and Automation.

[22]  Donald D. Dudenhoeffer,et al.  A Robotic Swarm for Spill Finding and Perimeter Formation , 2002 .