Enwei Chen

Application of ANN in Identification of Inertial Parameters of End-Effector of Robot

Identification of inertial parameters of manipulator of a robot is an important basic problem in robot dynamical research. Algorithm and mathematical model of inertial parameters identification of robot are analyzed in this paper. General rules and advantages of application of artificial neural network in identification of parameters of system are investigated also. A novel method different from the traditional ANN problems is developed. The structure and the weights of the network constructed have special physical meanings in this method. Difficulty in obtaining the training samples, which exists in the traditional ANN for inertial parameters estimation, is resolved. This method is simple, direct and less in operand, which can be applied on the end-effector of a robot on line to estimate its inertial parameters based on the signal of sensors. Feasibility and effectiveness of this method are proved by the results of experiment carried out in a PUMA 562 robot.

A method for measuring dynamic performance index of robot's multi-axis wrist force sensor

A novel method based correlation wavelet for online dynamic characteristic analysis and measurement of dynamic performance index of robot wrist sensor is developed in this paper. Based on the dynamic model of the force sensor, the simulations on the correlation wavelet method for extracting the IRF of wrist force sensor in two dynamic environments are presented. The simulation results show that the correlation wavelet method exhibits obvious advantages compared with the traditional FFT method, and the accuracy of the results is greatly improved. A test with cantilever under step excitation is carried out, the results obtained by using CWT method show that the method is effective and accurate. The way for generating step excitation automatically in robotic use is proposed for on-line dynamic characteristic analysis and measurement of dynamic performance index of robot wrist sensor. An example is given to illustrate the feature of the method. The method developed in the paper provides a new and effective way to measure the dynamic performance index of robot wrist force sensor, as well as other sensors.

ANALYSIS ON THE INFLUENCE OF MODELING ERRORS ON SENSOR DYNAMIC COMPENSATION

The relationship between modeling error of the system and widening multiple of the working frequency band was analyzed quantitatively and its spectrums were obtained. They offered a criterion to estimate the feasibility and effect in engineering practice of the compensating method to improve the sensors dynamic characteristics, and proved that the compensating method has good reliability. Conclusions were drawn clearly: For a first-order system, the compensation effect is conspicuous, which only relates to modeling error but is independent of time constant; for a second-order system, the compensation effect is determined by modeling error and damping ratio. Within a wide range, if the damping ratio is larger, the modeling precision required to obtain the same compensation effect can be lower. Through quantitatively analysis, we found that the modeling precision in dynamic compensation with analogy or digital filter should not be so high as one is taken for granted currently.