TY - GEN
T1 - Real-time filtering method based on neuron filtering mechanism and its application on robot speed signals
AU - Gao, Wa
AU - Zha, Fusheng
AU - Song, Baoyu
AU - Li, Mantian
AU - Wang, Pengfei
AU - Jiang, Zhenyu
AU - Guo, Wei
PY - 2014
Y1 - 2014
N2 - In order to implement the real-time filtering and tracking of robot signals with high efficiency, a novel real-time filtering method based on neuron filtering mechanism is developed in this paper. By considering the ubiquity of resonance in mammal and combining the mechanism of neural information processing, the derived details and the feasible parameter criterion under minimum error variance condition are given. For illustration, the application on quadruped robot is discussed. The quadruped robot feet speed signals are processed by developed real-time filtering method and Kalman filtering algorithm, respectively, and the computation time of both methods is tested. Experiment results show that the performance of developed real-time filtering method is better than that of Kalman filtering algorithm, not only in filtering and tracking performance but also in filtering speed. The novel real-time filtering method based on neuron filtering mechanism can effectively implement the real-time filtering and tracking with regard to robot signals.
AB - In order to implement the real-time filtering and tracking of robot signals with high efficiency, a novel real-time filtering method based on neuron filtering mechanism is developed in this paper. By considering the ubiquity of resonance in mammal and combining the mechanism of neural information processing, the derived details and the feasible parameter criterion under minimum error variance condition are given. For illustration, the application on quadruped robot is discussed. The quadruped robot feet speed signals are processed by developed real-time filtering method and Kalman filtering algorithm, respectively, and the computation time of both methods is tested. Experiment results show that the performance of developed real-time filtering method is better than that of Kalman filtering algorithm, not only in filtering and tracking performance but also in filtering speed. The novel real-time filtering method based on neuron filtering mechanism can effectively implement the real-time filtering and tracking with regard to robot signals.
UR - https://www.scopus.com/pages/publications/84958546868
U2 - 10.1007/978-3-319-01766-2_111
DO - 10.1007/978-3-319-01766-2_111
M3 - 会议稿件
AN - SCOPUS:84958546868
SN - 9783319017655
T3 - Lecture Notes in Electrical Engineering
SP - 971
EP - 978
BT - Computer Engineering and Networking - Proceedings of the 2013 International Conference on Computer Engineering and Network, CENet 2013
PB - Springer Verlag
T2 - 3rd International Conference on Computer Engineering and Network, CENet 2013
Y2 - 20 July 2013 through 21 July 2013
ER -