Title :
Adaptive visual servoing using curve features with unknown geometrical parameters
Author :
Maojiao Cai ; Hesheng Wang ; Weidong Chen
Author_Institution :
Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
This paper presents a novel curve image feature description using cubic Bezier curve, which extends the depth-independent image Jacobian matrix to curve features. We derive the image Jacobian matrix that can be linearly parameterized by the unknown curve feature geometrical parameters in the 3-D space. To estimate the unknown parameters online, we propose an adaptive algorithm using the defined curve image features. The control law is designed and the asymptotic stability is analyzed by the Lyapunov theory. There is no need to known the curve parameters or do correspondence matching while visual servoing. Experiment has been conducted to demonstrate the performance of the proposed controller with the curve features.
Keywords :
Jacobian matrices; Lyapunov methods; asymptotic stability; curve fitting; image matching; visual servoing; Lyapunov theory; adaptive algorithm; adaptive visual servoing; asymptotic stability; control law design; cubic Bezier curve; curve feature geometrical parameter; curve image feature description; curve parameter; depth-independent image Jacobian matrix; Cameras; Estimation; Jacobian matrices; Visual servoing; Visualization;
Conference_Titel :
Robotics and Biomimetics (ROBIO), 2014 IEEE International Conference on
DOI :
10.1109/ROBIO.2014.7090569