International Journal of Systems, Control and Communications
Neural network control of mobile robot formations using RISE feedback
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Leader-follower formation control of underactuated AUVs with leader position measurement
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Multi-robot plan adaptation by constrained minimal distortion feature mapping
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
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
Agent formations in 3D spaces with communication limitations using an adaptive Q-structure
Robotics and Autonomous Systems
Neighborhood linear embedding for intrinsic structure discovery
Machine Vision and Applications
Flexible formation of the multi-robot system and its application on CMOMMT problem
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 1
Attractor dynamics approach to formation control: theory and application
Autonomous Robots
Cellular ants: A method to create collision free trajectories for a cooperative robot team
Robotics and Autonomous Systems
Decision making as optimization in multi-robot teams
ICDCIT'12 Proceedings of the 8th international conference on Distributed Computing and Internet Technology
Pareto-optimal coordination of multiple robots with safety guarantees
Autonomous Robots
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In this paper, we present a novel approach for representing formation structures in terms of queues and formation vertices, rather than with nodes, as well as the introduction of the new concept of artificial potential trenches, for effectively controlling the formation of a group of robots. The scheme improves the scalability and flexibility of robot formations when the team size changes, and at the same time, allows formations to adapt to obstacles. Furthermore, for multirobot teams to operate successfully in real and unstructured environments, the instant goal method is used to effectively solve the local minima problem.