Open Access System for Information Sharing

Login Library

 

Article
Cited 17 time in webofscience Cited 19 time in scopus
Metadata Downloads

Real-time dynamic visual tracking using PSD sensors and extended trapezoidal motion planning SCIE SCOPUS

Title
Real-time dynamic visual tracking using PSD sensors and extended trapezoidal motion planning
Authors
Nam, SHOh, SY
Date Issued
1999-01
Publisher
KLUWER ACADEMIC PUBL
Abstract
A real-time visual servo tracking system for an industrial robot has been implemented using PSD (Position Sensitive Detector) cameras, neural networks, and an extended trapezoidal motion planning method. PSD and directly transduces the light's projected position on its sensor plane into an analog current and lends itself to fast real-time tracking. A neural network, after proper training, transforms the PSD sensor reading into a 3D position of the target, which is then input to an extended trapezoidal motion planning algorithm. This algorithm implements a continuous motion update strategy in response to an ever-changing sensor information from the moving target, while greatly reducing the tracking delay. This planning method is found to be very useful for sensor-based control such as moving target tracking or weld-seam tracking in which the robot needs to change its motion in real time in response to incoming sensor information. Further, for real-time usage of the neural net, a new architecture called LANN (Locally Activated Neural Network) has been developed based on the concept of CMAC input partitioning and local learning. Experimental evidence shows that an industrial robot can smoothly track a moving target of unknown motion with speeds of up to 1 m/s and with oscillation frequency up to 5 Hz.
Keywords
visual servoing; target tracking; position sensitive detectors; extended trapezoidal motion planning; locally activated neural network; MOTOR-COORDINATION; NEURAL CONTROLLER; NETWORK; SYSTEMS; ROBOT
URI
https://oasis.postech.ac.kr/handle/2014.oak/20480
DOI
10.1023/A:1008385515068
ISSN
0924-669X
Article Type
Article
Citation
APPLIED INTELLIGENCE, vol. 10, no. 1, page. 53 - 70, 1999-01
Files in This Item:
There are no files associated with this item.

qr_code

  • mendeley

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher

오세영OH, SE YOUNG
Dept of Electrical Enginrg
Read more

Views & Downloads

Browse