Visual feedback control of a robot in an unknown environment (learning control using neural networks)
Source: The International Journal of Advanced Manufacturing Technology, Volume 24, Numbers 7-8, October 2004 , pp. 509-516(8)
Abstract:In this paper, a visual feedback control approach based on neural networks is presented for a robot with a camera installed on its end-effector to trace an object in an unknown environment. First, the one-to-one mapping relations between the image feature domain of the object to the joint angle domain of the robot are derived. Second, a method is proposed to generate a desired trajectory of the robot by measuring the image feature parameters of the object. Third, a multilayer neural network is used for off-line learning of the mapping relations so as to produce on-line the reference inputs for the robot. Fourth, a learning controller based on a multilayer neural network is designed for realizing the visual feedback control of the robot. Last, the effectiveness of the present approach is verified by tracing a curved line using a 6-degrees-of-freedom robot with a CCD camera installed on its end-effector. The present approach does not necessitate the tedious calibration of the CCD camera and the complicated coordinate transformations.
Document Type: Research Article
Affiliations: 1: School of Computer Engineering and Technology, South China University of Technology, Guangzhou, 510641, P.R. China, Email: email@example.com 2: School of Engineering and Technology, Deakin University, Geelong Victoria, 3217, Australia,
Publication date: October 1, 2004