Self-calibration method for pulse-3D terrestrial laser scanner based on least-square collocation

2021 ◽  
Vol 29 (4) ◽  
pp. 665-673
Author(s):  
Xian-tao GUO ◽  
◽  
Yan JIA
Keyword(s):  
Laser Scanner ◽  
Calibration Method ◽  
Least Square ◽  
Terrestrial Laser Scanner ◽  
Self Calibration ◽  
Least Square Collocation

scholarly journals Self-Calibration of an Industrial Robot Using a Novel Affordable 3D Measuring Device

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3380 ◽  
Author(s):  
Martin Gaudreault ◽  
Ahmed Joubair ◽  
Ilian Bonev
Keyword(s):  
Industrial Robot ◽  
Low Cost ◽  
Least Square Method ◽  
Calibration Method ◽  
Least Square ◽  
Geometrical Parameters ◽  
Robot Arm ◽  
Measuring Device ◽  
Self Calibration ◽  
Position Errors

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.

scholarly journals Lab-built terrestrial laser scanner self-calibration using mounting angle error correction

2018 ◽  
Vol 26 (11) ◽  
pp. 14444 ◽  
Author(s):  
Xiaolu Li ◽  
Yunye Li ◽  
Xinhao Xie ◽  
Lijun Xu
Keyword(s):  
Error Correction ◽  
Laser Scanner ◽  
Terrestrial Laser Scanner ◽  
Angle Error ◽  
Self Calibration

Self-calibration of three-legged modular reconfigurable parallel robots based on leg-end distance errors

Robotica ◽  
2001 ◽  
Vol 19 (2) ◽  
pp. 187-198 ◽  
Author(s):  
Guilin Yang ◽  
I-Ming Chen ◽  
Wee Kiat Lee ◽  
Song Huat Yeo
Keyword(s):  
Calibration Method ◽  
Parallel Robots ◽  
Least Square ◽  
Fine Tuning ◽  
Robot Kinematics ◽  
Calibration Model ◽  
Kinematic Calibration ◽  
Linear Calibration ◽  
Self Calibration ◽  
End Distance

A class of three-legged modular reconfigurable parallel robots is designed and constructed for precision assembly and light machining tasks by using standard active and passive joint modules in conjunction with custom designed links and mobile platforms. Since kinematic errors, especially the assembly errors, are likely to be introduced, kinematic calibration becomes particularly important to enhance the positioning accuracy of a modular reconfigurable robot. Based on the local frame representation of the Product-Of-Exponentials (Local POE) formula, a self-calibration method is proposed for these three-legged modular reconfigurable parallel robots. In this method, both revolute and prismatic joint axes can be uniformly expressed in twist coordinates by their respective local (body) frames. Since these local frames can be arbitrarily defined on their corresponding links, we are able to calibrate them, and yet retain the nominal local description of their respective joints, i.e., the nominal twist coordinates and nominal joint displacements, to reflect the actual kinematics of the robot. The kinematic calibration thus becomes a procedure of fine-tuning the locations and orientations of the local frames. Using mathematical tools from differential geometry and group theory, an explicit linear calibration model is formulated based on the leg-end distance errors. An iterative least-square algorithm is employed to identify the error parameters. A simulation example of calibrating a three-legged (RRRS) modular parallel robot shows that the robot kinematics can be fully calibrated within two to three iterations.

scholarly journals DOA Estimation and Self-Calibration under Unknown Mutual Coupling

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 978
Author(s):  
Dong Qi ◽  
Min Tang ◽  
Shiwen Chen ◽  
Zhixin Liu ◽  
Yongjun Zhao
Keyword(s):  
Mutual Coupling ◽  
Linear Equations ◽  
Least Square Method ◽  
Calibration Method ◽  
Least Square ◽  
Frequency Distributions ◽  
Steering Vector ◽  
Practical Applications ◽  
Time Frequency ◽  
Self Calibration

In practical applications, the assumption of omnidirectional elements is not effective in general, which leads to the direction-dependent mutual coupling (MC). Under this condition, the performance of traditional calibration algorithms suffers. This paper proposes a new self-calibration method based on the time-frequency distributions (TFDs) in the presence of direction-dependent MC. Firstly, the time-frequency (TF) transformation is used to calculate the space-time-frequency distributions (STFDs) matrix of received signals. After that, the estimated steering vector and corresponding noise subspace are estimated by the steps of noise removing, single-source TF points extracting and clustering. Then according to the transformation relationship between the MC coefficients, steering vector and MC matrix, we deduce a set of linear equations. Finally, with two-step alternating iteration, the equations are solved by least square method in order to estimate DOA and MC coefficients. Simulations results show that the proposed algorithm can achieve direction-dependent MC self-calibration and outperforms the existing algorithms.

scholarly journals Least Squares 3D Algorithm for the Study of Deformations with Terrestrial Laser Scanner

2021 ◽  
Vol 15 ◽  
pp. 53-56
Author(s):  
Vincenzo Barrile ◽  
Giuseppe M. Meduri ◽  
Giuliana Bilotta
Keyword(s):  
Least Squares ◽  
Laser Scanner ◽  
Point Clouds ◽  
Least Square ◽  
Surface Matching ◽  
Data Sets ◽  
Terrestrial Laser Scanner ◽  
Mountain Areas ◽  
Hilly Area ◽  
T1 And T2

The application in question is aimed, in the study of deformations of mountain areas, as well as test the TLS applied to a hilly area in two different eras. For this purpose, it was also tested using the algorithm LS3D “Least square 3D surface matching” that allows both the registration of point clouds produced by scans carried out without using targets but, overall, the estimate of deformations that in this case, compared to other methods, is done directly on the basis of the two data sets acquired in two different periods of time t1 and t2.

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