Operations Research, Systems Engineering and Industrial Engineering Commons^™

Uncalibrated Visual Servoing Based On Kalman Filter Optimized By Spsa, Jinqiang Zhang, Xianxia Zhang

Journal of System Simulation

Abstract: Considering the problem of robot uncalibrated visual servoing, this paper presents a method for online estimation of image Jacobian matrix based on Kalman filter optimized by simultaneous perturbation stochastic approximation algorithm. This method takes the robot image Jacobian matrix as the system state, and uses Kalman filter to observe the system state. In order to improve the performance of the filter, the simultaneous perturbation stochastic approximation algorithm is used to optimize the filter parameters. This method is used to estimate the image Jacobian matrix and to design the control strategy, which can avoid complicated system calibration process. The simulation …

Calibration Of Microscopic Traffic Flow Models Considering All Parameters Simultaneously, Victor Hugo Molano Paz

UNLV Theses, Dissertations, Professional Papers, and Capstones

This study proposes a methodology to calibrate microscopic traffic flow simulation models. The proposed methodology has the capability to calibrate simultaneously all the calibration parameters as well as demand patterns for any network topology. These parameters include global and local parameters as well as driver behavior and vehicle performance parameters; all based on multiple performance measures, such as link counts and speeds. Demand patterns are included in the calibration framework in terms of turning volumes.

A Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm is proposed to search for the vector of the model‟s parameters that minimizes the difference between actual and …