A Kinematic Calibration Method of the Articulated Arm Coordinate Measuring Machine Using Niching Chaos Optimization Algorithm

2018 ◽  
Vol 48 (4) ◽  
pp. 20180174
Author(s):  
Cholmin Rim ◽  
Chang-Hyon Rim ◽  
Gang Chen ◽  
Yongchol Sin ◽  
Kukchol Kim
Keyword(s):  
Optimization Algorithm ◽  
Coordinate Measuring Machine ◽  
Calibration Method ◽  
Kinematic Calibration ◽  
Chaos Optimization ◽  
Chaos Optimization Algorithm ◽  
Measuring Machine

Calibration method of PCMA by using niching chaos optimization algorithm

2018 ◽  
Vol 26 (8) ◽  
pp. 2048-2056
Author(s):  
林苍现 RIM Chang-Hyon ◽  
林哲民 RIM Chol-Min ◽  
陈 刚 CHEN Gang ◽  
李评哲 RI Pyong-Chol
Keyword(s):  
Optimization Algorithm ◽  
Calibration Method ◽  
Chaos Optimization ◽  
Chaos Optimization Algorithm

CCD Camera Calibration Technology Based on the Translation of Coordinate Measuring Machine

2014 ◽  
Vol 568-570 ◽  
pp. 320-325 ◽  
Author(s):  
Feng Shan Huang ◽  
Li Chen
Keyword(s):  
Coordinate System ◽  
Camera Calibration ◽  
Characteristic Point ◽  
Coordinate Measuring Machine ◽  
Ccd Camera ◽  
Mathematic Model ◽  
Calibration Method ◽  
Calibration Characteristic ◽  
Standard Sphere ◽  
Measuring Machine

A new CCD camera calibration method based on the translation of Coordinate Measuring Machine (CMM) is proposed. The CMM brings the CCD camera to produce the relative translation with respect to the center of the white ceramic standard sphere along the X, Y, Z axis, and the coordinates of the different positions of the calibration characteristic point in the probe coordinate system can be generated. Meanwhile, the camera captures the image of the white ceramic standard sphere at every position, and the coordinates of the calibration characteristic point in the computer frame coordinate system can be registered. The calibration mathematic model was established, and the calibration steps were given and the calibration system was set up. The comparing calibration result shows that precision of this method is equivalent to that of the special calibration method, and the difference between the calibrating data of these two methods is within ±1μm.

A new approach of kinematic geometry for error identification and compensation of industrial robots

2018 ◽  
Vol 233 (5) ◽  
pp. 1783-1794
Author(s):  
Zhi Wang ◽  
Huimin Dong ◽  
Shaoping Bai ◽  
Delun Wang
Keyword(s):  
Curve Fitting ◽  
Kinematic Model ◽  
Coordinate Measuring Machine ◽  
Reference Points ◽  
Industrial Robots ◽  
Kinematic Calibration ◽  
Kinematic Pair ◽  
Good Efficiency ◽  
New Approach ◽  
Measuring Machine

A new approach for kinematic calibration of industrial robots, including the kinematic pair errors and the link errors, is developed in this paper based on the kinematic invariants. In most methods of kinematic calibration, the geometric errors of the robots are considered in forms of variations of the link parameters, while the kinematic pairs are assumed ideal. Due to the errors of mating surfaces in kinematic pairs, the fixed and moving axes of revolute pairs, or the fixed and moving guidelines of prismatic pairs, are separated, which can be concisely identified as the kinematic pair errors and the link errors by means of the kinematic pair errors model, including the self-adaption fitting of a ruled surface, or the spherical image curve fitting and the striction curve fitting. The approach is applied to the kinematic calibration of a SCARA robot. The discrete motion of each kinematic pair in the robot is completely measured by a coordinate measuring machine. Based on the global kinematic properties of the measured motion, the fixed and moving axes, or guidelines, of the kinematic pairs are identified, which are invariants unrelated to the positions of the measured reference points. The kinematic model of the robot is set up using the identified axes and guidelines. The results validate the approach developed has good efficiency and accuracy.

Application of Parallel Chaos Optimization Algorithm for Plug-in Hybrid Electric Vehicle Design

2014 ◽  
Vol 24 (01) ◽  
pp. 1450001 ◽  
Author(s):  
Xiaolan Wu ◽  
Guifang Guo ◽  
Jun Xu ◽  
Binggang Cao
Keyword(s):  
Optimization Algorithm ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Optimization Problem ◽  
Optimization Method ◽  
Vehicle Performance ◽  
Chaos Optimization ◽  
Performance Requirements ◽  
Chaos Optimization Algorithm ◽  
Hybrid Electric

Plug-in hybrid electric vehicles (PHEVs) have been offered as alternatives that could greatly reduce fuel consumption relative to conventional vehicles. A successful PHEV design requires not only optimal component sizes but also proper control strategy. In this paper, a global optimization method, called parallel chaos optimization algorithm (PCOA), is used to optimize simultaneously the PHEV component sizes and control strategy. In order to minimize the cost, energy consumption (EC), and emissions, a multiobjective nonlinear optimization problem is formulated and recast as a single objective optimization problem by weighted aggregation. The driving performance requirements of the PHEV are considered as the constraints. In addition, to evaluate the objective function, the optimization process is performed over three typical driving cycles including Urban Dynamometer Driving Schedule (UDDS), Highway Fuel Economy Test (HWFET), and New European Driving Cycle (NEDC). The simulation results show the effectiveness of the proposed approach for reducing the fuel cost, EC and emissions while ensuring that the vehicle performance has not been sacrificed.

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