Automatica (Journal of IFAC)
Brief paper: Region-based shape control for a swarm of robots
Automatica (Journal of IFAC)
Globally stable adaptive formation control of Euler-Lagrange agents via potential functions
ACC'09 Proceedings of the 2009 conference on American Control Conference
Swarm formation control utilizing elliptical surfaces and limiting functions
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Effective robot team control methodologies for battlefield applications
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Coordination and control of multi-agent dynamic systems: models and approaches
SAB'06 Proceedings of the 2nd international conference on Swarm robotics
Attractor dynamics approach to formation control: theory and application
Autonomous Robots
Distributed reactive collision avoidance
Autonomous Robots
Image and animation display with multiple mobile robots
International Journal of Robotics Research
Automatica (Journal of IFAC)
Multilevel-based topology design and shape control of robot swarms
Automatica (Journal of IFAC)
Formation Control of Multiple Groups of Nonholonomic Wheeled Mobile Robots
Proceedings of Conference on Advances In Robotics
Hi-index | 0.01 |
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.