Swarm aggregations using artificial potentials and sliding-mode control

In this paper, we consider a control strategy of multiagent systems, or simply, swarms, based on artificial potential functions and the sliding-mode control technique. First, we briefly discuss a "kinematic" swarm model in n-dimensional space introduced in an earlier paper. In that model, the interindividual interactions are based on artificial potential functions, and the motion of the individuals is along the negative gradient of the combined potential. After that, we consider a general model for vehicle dynamics of each agent (swarm member), and use sliding-mode control theory to force their motion to obey the dynamics of the kinematic model. In this context, the results for the initial model serve as a "proof of concept" for multiagent coordination and control (swarm aggregation), whereas the present results serve as a possible implementation method for engineering swarms with given vehicle dynamics. The presented control scheme is robust with respect to disturbances and system uncertainties.

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

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

[3]  V. I. Utkin,et al.  Sliding mode control for an obstacle avoidance strategy based on an harmonic potential field , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[4]  R. Decarlo,et al.  Variable structure control of nonlinear multivariable systems: a tutorial , 1988, Proc. IEEE.

[5]  Hongyan Wang,et al.  Social potential fields: A distributed behavioral control for autonomous robots , 1995, Robotics Auton. Syst..

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

[7]  Kevin M. Passino,et al.  Stability analysis of swarms , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[8]  Kevin M. Passino,et al.  Stability analysis of swarms in an environment with an attractant/repellent profile , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[9]  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..

[10]  Vadim I. Utkin,et al.  Robot path obstacle avoidance control via sliding mode approach , 1991, Proceedings IROS '91:IEEE/RSJ International Workshop on Intelligent Robots and Systems '91.

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

[12]  Veysel Gazi,et al.  Target tracking using artificial potentials and sliding mode control , 2004 .

[13]  Hiroaki Yamaguchi,et al.  A Cooperative Hunting Behavior by Mobile-Robot Troops , 1999, Int. J. Robotics Res..

[14]  Naomi Ehrich Leonard,et al.  Virtual Leaders, Artificial Potentials Control of Groups' , 2001 .

[15]  Raúl Ordóñez,et al.  Target tracking using artificial potentials and sliding mode control , 2007, Proceedings of the 2004 American Control Conference.

[16]  V. Gazi *,et al.  Formation control of a multi-agent system using non-linear servomechanism , 2005 .

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

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

[19]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1986 .

[20]  Veysel Gazi,et al.  Swarm aggregations using artificial potentials and sliding mode control , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[21]  Marios M. Polycarpou,et al.  Stability analysis of one-dimensional asynchronous mobile swarms , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[22]  V. Gazi Formation control of a multi-agent system using non-linear servomechanism , 2005 .

[23]  Veysel Gazi,et al.  Formation control of a multi-agent system using decentralized nonlinear servomechanism , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[24]  Kevin M. Passino,et al.  Stability of a one-dimensional discrete-time asynchronous swarm , 2001, Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206).

[25]  K. Passino,et al.  A class of attractions/repulsion functions for stable swarm aggregations , 2004 .

[26]  Vijay Kumar,et al.  Modeling and control of formations of nonholonomic mobile robots , 2001, IEEE Trans. Robotics Autom..

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

[28]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1985, Autonomous Robot Vehicles.

[29]  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..

[30]  Kevin M. Passino,et al.  Stability of a one-dimensional discrete-time asynchronous swarm , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

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

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

[33]  J. Guldner,et al.  Sliding mode control for gradient tracking and robot navigation using artificial potential fields , 1995, IEEE Trans. Robotics Autom..

[34]  Vijay Kumar,et al.  Controlling formations of multiple mobile robots , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).