Decentralized control of large scale systems
Three decades of mathematical system theory
Moving furniture with teams of autonomous robots
IROS '95 Proceedings of the International Conference on Intelligent Robots and Systems-Volume 1 - Volume 1
International Journal of Robotics Research
Error characterization in the vicinity of singularities in multi-robot cluster space control
ROBIO '09 Proceedings of the 2008 IEEE International Conference on Robotics and Biomimetics
Teleo-reactive programs for agent control
Journal of Artificial Intelligence Research
Entrapment/escorting and patrolling missions in multi-robot cluster space control
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Decentralized overlapping control of a formation of unmanned aerial vehicles
Automatica (Journal of IFAC)
Distributed receding horizon control for multi-vehicle formation stabilization
Automatica (Journal of IFAC)
Entrapment/escorting and patrolling missions in multi-robot cluster space control
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
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The cluster space state representation for multi-robot systems provides a simple means of specifying and monitoring the geometry and motion characteristics of a cluster of mobile robots. In previous work, this approach has been experimentally verified and validated for controlling the motion of mobile multi-robot systems ranging from land rovers to autonomous boats. In this paper we introduce a compact collision avoidance algorithm that operates at the level of the cluster, leading to coordinated translational and rotational motions that allow obstacles to be avoided while maintaining the relative geometry of the cluster. This paper formulates the potential-field based obstacle avoidance algorithm, describes its integration within the cluster space control architecture, and presents successful experimental results of its application to two simple, diverse multi-robot testbeds.