A self-calibration method with high-accuracy and low-cost for large-area motion stage based on digital grating projection mode

2019 ◽  
Vol 12 (12) ◽  
pp. 126503
Author(s):  
Shengzhou Huang ◽  
Mujun Li ◽  
Lei Wang ◽  
Yongsheng Su ◽  
Yi Liang
2017 ◽  
Author(s):  
Guo Wei ◽  
Chunfeng Gao ◽  
Qi Wang ◽  
Qun Wang ◽  
Xingwu Long

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3380 ◽  
Author(s):  
Martin Gaudreault ◽  
Ahmed Joubair ◽  
Ilian Bonev

This work shows the feasibility of calibrating an industrial robot arm through an automated procedure using a new, low-cost, wireless measuring device mounted on the robot’s flange. The device consists of three digital indicators that are fixed orthogonally to each other on an aluminum support. Each indicator has a measuring accuracy of 3 µm. The measuring instrument uses a kinematic coupling platform which allows for the definition of an accurate and repeatable tool center point (TCP). The idea behind the calibration method is for the robot to bring automatically this TCP to three precisely-known positions (the centers of three precision balls fixed with respect to the robot’s base) and with different orientations of the robot’s end-effector. The self-calibration method was tested on a small six-axis industrial robot, the ABB IRB 120 (Vasteras, Sweden). The robot was modeled by including all its geometrical parameters and the compliance of its joints. The parameters of the model were identified using linear regression with the least-square method. Finally, the performance of the calibration was validated with a laser tracker. This validation showed that the mean and the maximum absolute position errors were reduced from 2.628 mm and 6.282 mm to 0.208 mm and 0.482 mm, respectively.


Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1624 ◽  
Author(s):  
Yao Xiao ◽  
Xiaogang Ruan ◽  
Jie Chai ◽  
Xiaoping Zhang ◽  
Xiaoqing Zhu

Low-cost microelectro mechanical systems (MEMS)-based inertial measurement unit (IMU) measurements are usually affected by inaccurate scale factors, axis misalignments, and g-sensitivity errors. These errors may significantly influence the performance of visual-inertial methods. In this paper, we propose an online IMU self-calibration method for visual-inertial systems equipped with a low-cost inertial sensor. The goal of our method is to concurrently perform 3D pose estimation and online IMU calibration based on optimization methods in unknown environments without any external equipment. To achieve this goal, we firstly develop a novel preintegration method that can handle the IMU intrinsic parameters error propagation. Then, we frame IMU calibration problem into general factors so that we can easily integrate the factors into the current graph-based visual-inertial frameworks and jointly optimize the IMU intrinsic parameters as well as the system states in a big bundle. We evaluate the proposed method with a publicly available dataset. Experimental results verify that the proposed approach is able to accurately calibrate all the considered parameters in real time, leading to significant improvement of estimation precision of visual-inertial system (VINS) compared with the estimation results with offline precalibrated IMU measurements.


2012 ◽  
Vol 503-504 ◽  
pp. 1265-1269
Author(s):  
Xiu Xiang Huang ◽  
Qing Tan ◽  
Yi Min Xia ◽  
Ze Yuan Liu ◽  
Lei Cai

Calibration is crucial to the accuracy of grating measurement, which directly determines the accuracy of the measurement. The traditional calibration principle is easily influenced by some factors in projection measurement for lack of flexibility. This paper presents a new calibration method by using and improving Zhang’s Calibration Method, by which high accuracy and efficiency are achieved with low cost.


2020 ◽  
Vol 86 (3) ◽  
pp. 169-176
Author(s):  
Shuo Zhang ◽  
Yang Jia ◽  
Song Peng ◽  
Bo Wen ◽  
Youqing Ma ◽  
...  

The stereo vision system is the special engineering measurement instrument of the Chang'e-4 lunar rover. It is composed of the Navigation Camera (NavCam) and the Mast Mechanism (MasMec). An improved self-calibration method for the stereo vision system of the Chang'e-4 lunar rover is proposed. The method consists of two parts: the NavCam's self-calibration and the MasMec's self-calibration. A combined adjustment based on the points and lines is proposed. The baseline constraint of the NavCam is considered. The self-calibration model of the MasMec is established based on the product-of-exponentials formula. Finally, the premission laboratory calibration and the on-site calibration are carried out. The laboratory calibration shows that the proposed approach has high accuracy. The checkpoint with a distance of about 2.7 m to the left NavCam has a point error of about 4 mm. Finally, the proposed approach is applied in the on-site calibration.


2020 ◽  
Vol 13 (5) ◽  
pp. 056501
Author(s):  
Shengzhou Huang ◽  
Mujun Li ◽  
Lei Wang ◽  
Yongsheng Su ◽  
Fengtao Wang ◽  
...  

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