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Yang, Jackson C. S.

Publications and source records attributed to Yang, Jackson C. S..

An automated computerized vision technique for determination of three-dimensional object geometry

It is very important to determine three dimensional geometry of objects quickly in various military, space, construction, and industrial applications. An automatic scheme to obtain three dimensional geometry of objects by employing only one camera is presented. At present, this technique is applicable to a limited category of objects, satisfying the following constraints: they are flat-surfaces, and all the vertex points have to be recognized as corner points of the two dimensional image. The scheme consists of corner detection, data communication, camera calibration techniques and point searching and matching, edge cancelation, and creation procedures. An L shaped model is chosen as a test object. Experimental results demonstrated the reconstruction of this object geometry within 5 mm discrepancy. This scheme is quite convenient, efficient to use and can be applied to a wide range of problems in the real world.

Chiang, Pen-Tai↗

A system identification technique based on the random decrement signatures. Part 1: Theory and simulation

Identification of the system parameters of a randomly excited structure may be treated using a variety of statistical techniques. Of all these techniques, the Random Decrement is unique in that it provides the homogeneous component of the system response. Using this quality, a system identification technique was developed based on a least-squares fit of the signatures to estimate the mass, damping, and stiffness matrices of a linear randomly excited system. The mathematics of the technique is presented in addition to the results of computer simulations conducted to demonstrate the prediction of the response of the system and the random forcing function initially introduced to excite the system.

Bedewi, Nabih E.↗

A system identification technique based on the random decrement signatures. Part 2: Experimental results

Identification of the system parameters of a randomly excited structure may be treated using a variety of statistical techniques. Of all these techniques, the Random Decrement is unique in that it provides the homogeneous component of the system response. Using this quality, a system identification technique was developed based on a least-squares fit of the signatures to estimate the mass, damping, and stiffness matrices of a linear randomly excited system. The results of an experiment conducted on an offshore platform scale model to verify the validity of the technique and to demonstrate its application in damage detection are presented.

Bedewi, Nabih E.↗

Performance improvement of robots using a learning control scheme

Many applications of robots require that the same task be repeated a number of times. In such applications, the errors associated with one cycle are also repeated every cycle of the operation. An off-line learning control scheme is used here to modify the command function which would result in smaller errors in the next operation. The learning scheme is based on a knowledge of the errors and error rates associated with each cycle. Necessary conditions for the iterative scheme to converge to zero errors are derived analytically considering a second order servosystem model. Computer simulations show that the errors are reduced at a faster rate if the error rate is included in the iteration scheme. The results also indicate that the scheme may increase the magnitude of errors if the rate information is not included in the iteration scheme. Modification of the command input using a phase and gain adjustment is also proposed to reduce the errors with one attempt. The scheme is then applied to a computer model of a robot system similar to PUMA 560. Improved performance of the robot is shown by considering various cases of trajectory tracing. The scheme can be successfully used to improve the performance of actual robots within the limitations of the repeatability and noise characteristics of the robot.

Krishna, Ramuhalli↗