Biologically-Inspired Learning and Adaptation of Self-Evolving Control for Networked Mobile Robots

Biologically-Inspired Learning and Adaptation of Self-Evolving Control for Networked Mobile Robots

This paper presents a biologically-inspired learning and adaptation method for self-evolving control of networked mobile robots. A Kalman filter (KF) algorithm is employed to develop a self-learning RBFNN (Radial Basis Function Neural Network), called the KF-RBFNN. The structure of the KF-RBFNN is o...

Full description

Bibliographic Details
Main Authors: Sendren Sheng-Dong Xu, Hsu-Chih Huang, Tai-Chun Chiu, Shao-Kang Lin
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Applied Sciences
Subjects:
biologically-inspired
self-learning
formation control
mobile robots
Online Access:http://www.mdpi.com/2076-3417/9/5/1034

Internet

http://www.mdpi.com/2076-3417/9/5/1034

Similar Items