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Proceedings Paper

Adaptive visual tracking of moving object with neural-PID controller
Author(s): Liucun Zhu; Hideo Fujimoto; Akihito Sano; Satoko Yamakawa
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Paper Abstract

In this paper, an adaptive approach is presented to nonlinear system for real-time robotic visual tracking of a moving polyhedral object. A light stripe vision system consists of a laser-stripe sensor and a CCD camera fixed to robot end-effector, and projects planar light on the polyhedral object. The geometric conditions can be provided to assure location of features of the polyhedral faces. The objective is to predict the location of features of the object on the image plane based on the light stripe vision system and then to determine an optimal control input that will move the camera so that the image features align with their desired positions. We first give the equations of observation and stat-space by using the motion rules of the camera and the object. Then, the system can be represented as an MIMO ARMAX model and an efficient estimation model. The estimation model can process on-line estimation of the 3D related parameters between the camera and the object. Those parameters are used to calculate the system sensitivity of a neural network. The control scheme adopts a neural-PID controller that can adjust the PID controller parameters. The paper concludes with the simulation results and the compute stimulation shows that the proposed method is effective to visual tracking of combining vision and control

Paper Details

Date Published: 11 October 2000
PDF: 12 pages
Proc. SPIE 4197, Intelligent Robots and Computer Vision XIX: Algorithms, Techniques, and Active Vision, (11 October 2000); doi: 10.1117/12.403779
Show Author Affiliations
Liucun Zhu, Nagoya Institute of Technology (Japan)
Hideo Fujimoto, Nagoya Institute of Technology (Japan)
Akihito Sano, Nagoya Institute of Technology (Japan)
Satoko Yamakawa, Nagoya Institute of Technology (Japan)


Published in SPIE Proceedings Vol. 4197:
Intelligent Robots and Computer Vision XIX: Algorithms, Techniques, and Active Vision
David P. Casasent, Editor(s)

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