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Distributed Containment Control for Multi-robot System Based on Binocular Vision and RBF Neural Network

원문정보

초록

영어

Aiming at the distributed containment control problem for multi-robot system with dynamic leaders, we use binocular vision as the sensing device, so firstly, a binocular visual model for dynamic target is established by introducing the pseudo depth variable, and it is used to provide real-time status information for the followers. Then, in the case that each follower can only get information from part of the leaders, even individual follower can not get any information from the leaders directly, the topological relationship among robots is built by using the graph theory. Once more, RBF neural networks are employed to approximate the uncertainties in the system model of followers, and L2 robust control laws are used to restrain the influences of the approximation errors. Finally, a simulation is carried out on multiple 2 degrees-of-freedom (DOF) robots, and results validate the designed controllers can drive the followers converge to the convex hull spanned by the leaders asymptotically and realize synchronization motion ultimately.

목차

Abstract
 1. Introduction
 2. System Description and Graph Theory
 3. Binocular Visual Servo Model
 4. Distributed Containment Control for Multi-robot System with Dynamic Leaders
  4.1. Design of Sliding Mode Controller Based on Binocular Vision
  4.2. Approximation of RBF Neural Network
 5. Simulation Research
 6. Conclusion
 Acknowledgements
 References

저자정보

  • Nuan Shao Key Lab of Industrial Computer Control Engineering of Hebei Province, College of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
  • Huiguang Li Key Lab of Industrial Computer Control Engineering of Hebei Province, College of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
  • Le Liu Key Lab of Industrial Computer Control Engineering of Hebei Province, College of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
  • Guoyou Li Key Lab of Industrial Computer Control Engineering of Hebei Province, College of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China

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