TY - GEN
T1 - On-line identification of robotic ubiquitous cognitive network with erasure channels
AU - Lu, Zhenyu
AU - Huang, Panfeng
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/4/20
Y1 - 2014/4/20
N2 - Nowadays the Robotic Ubiquitous Cognitive network (RUBICON) has raised great attentions in robotics area. In this paper we explore and first propose a timely identification method of RUBICON with erasure channels. Firstly, the complex cognitive network is simplified into a single close-loop communicating network for identification. Then inspired by the interactive cognitive method, we propose recursive network identification method containing feedback mechanism. Three key problems of this method - dense format of transmitting messages, selection of prior packet for identification and the detailed network identification procedure - and their solving methods are presented. Finally, we make a simulation about the parameters identification of RUBICON which contains 8 sensors/actuator nodes. The simulated results show that the proposed algorithm can balance the difference of the identification results for every sensor node and enhance the unique convergence effect.
AB - Nowadays the Robotic Ubiquitous Cognitive network (RUBICON) has raised great attentions in robotics area. In this paper we explore and first propose a timely identification method of RUBICON with erasure channels. Firstly, the complex cognitive network is simplified into a single close-loop communicating network for identification. Then inspired by the interactive cognitive method, we propose recursive network identification method containing feedback mechanism. Three key problems of this method - dense format of transmitting messages, selection of prior packet for identification and the detailed network identification procedure - and their solving methods are presented. Finally, we make a simulation about the parameters identification of RUBICON which contains 8 sensors/actuator nodes. The simulated results show that the proposed algorithm can balance the difference of the identification results for every sensor node and enhance the unique convergence effect.
UR - http://www.scopus.com/inward/record.url?scp=84949927129&partnerID=8YFLogxK
U2 - 10.1109/ROBIO.2014.7090586
DO - 10.1109/ROBIO.2014.7090586
M3 - 会议稿件
AN - SCOPUS:84949927129
T3 - 2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014
SP - 1737
EP - 1742
BT - 2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014
Y2 - 5 December 2014 through 10 December 2014
ER -