Potential-based flocking in multi-agent systems with limited angular fields of view

In this paper, the flocking problem in a network of double-integrator agents with angularly limited fields of view (FOV) is investigated. The conic-shaped angular FOVs impose sensing limitations on every agent in the network. To increase the sensing capability of agents and preserve network connectivity, the FOV of every agent rotates with a sufficiently fast angular velocity. The problem is formulated in the framework of distributed switched nonlinear systems to address the switching topology of the network. Potential-based control inputs are subsequently designed as a combination of alignment and attractive/repulsive forces, such that the velocity vector of each agent exponentially reaches a certain neighborhood of a given desired velocity vector and the inter-agent collision is avoided. The efficacy of the proposed control strategy is confirmed by the simulation results.

[1]  J.K. Hedrick,et al.  An overview of emerging results in cooperative UAV control , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[2]  Andrea Gasparri,et al.  Decentralized topology control for robotic networks with limited field of view sensors , 2012, 2012 American Control Conference (ACC).

[3]  Zhong-Ping Jiang,et al.  Flocking of Decentralized Multi-Agent Systems with Application to Nonholonomic Multi-Robots , 2008 .

[4]  Kostas Daniilidis,et al.  Vision-based control laws for distributed flocking of nonholonomic agents , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[5]  Jie Lin,et al.  Coordination of groups of mobile autonomous agents using nearest neighbor rules , 2003, IEEE Trans. Autom. Control..

[6]  Patrick Fabiani,et al.  Low-speed optic-flow sensor onboard an unmanned helicopter flying outside over fields , 2013, 2013 IEEE International Conference on Robotics and Automation.

[7]  Yue Wang,et al.  Cooperative Vision-Based Multi-Vehicle Dynamic Coverage Control for Underwater Applications , 2007, 2007 IEEE International Conference on Control Applications.

[8]  Xiaoming Hu,et al.  Multi-robot distributed visual consensus using epipoles , 2011, IEEE Conference on Decision and Control and European Control Conference.

[9]  Craig W. Reynolds.  Flocks, herds, and schools: a distributed behavioral model , 1998 .

[10]  Sebastian Thrun,et al.  Visibility-based Pursuit-evasion with Limited Field of View , 2004, Int. J. Robotics Res..

[11]  Martin Buss,et al.  Bio-inspired visual ego-rotation sensor for MAVs , 2012, Biological Cybernetics.

[12]  Andrea Garulli,et al.  Collective circular motion of multi-vehicle systems , 2008, Autom..

[13]  Juo-Yu Lee.  Exploiting Constrained Rotation for Localization of Directional Sensor Networks , 2008, 2008 International Wireless Communications and Mobile Computing Conference.

[14]  Reza Olfati-Saber,et al.  Flocking for multi-agent dynamic systems: algorithms and theory , 2006, IEEE Transactions on Automatic Control.

[15]  Magnus Egerstedt,et al.  Laplacian Sheep: A Hybrid, Stop-Go Policy for Leader-Based Containment Control , 2006, HSCC.

[16]  Nathan Michael,et al.  Vision-Based, Distributed Control Laws for Motion Coordination of Nonholonomic Robots , 2009, IEEE Transactions on Robotics.