scholarly journals Exit Point, Initial Length and Pose Self-calibration Method for Cable-Driven Parallel Robots

2021 ◽  
pp. 90-101
Author(s):  
Bozhao Wang ◽  
Stéphane Caro
Keyword(s):  
Calibration Method ◽  
Parallel Robots ◽  
Exit Point ◽  
Initial Length ◽  
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.

A self-calibration method for rotary tables’ five degrees-of-freedom error motions

Measurement ◽  
2021 ◽  
Vol 174 ◽  
pp. 109067
Author(s):  
Zhi-Feng Lou ◽  
Li Liu ◽  
Ji-Yun Zhang ◽  
Kuang-chao Fan ◽  
Xiao-Dong Wang
Keyword(s):  
Degrees Of Freedom ◽  
Calibration Method ◽  
Self Calibration

scholarly journals A Vision-Based Self-Calibration Method for Robotic Visual Inspection Systems

Sensors ◽  
2013 ◽  
Vol 13 (12) ◽  
pp. 16565-16582 ◽  
Author(s):  
Shibin Yin ◽  
Yongjie Ren ◽  
Jigui Zhu ◽  
Shourui Yang ◽  
Shenghua Ye
Keyword(s):  
Visual Inspection ◽  
Calibration Method ◽  
Self Calibration ◽  
Inspection Systems

A Non-Intrusive Self-Calibration Method for the Circuit Design of Inductorless Low Noise Amplifier

2021 ◽  
Author(s):  
Wenrun Xiao ◽  
Weikang Wu ◽  
Yinghui Chang ◽  
Jidong Diao ◽  
Yanping Qiao ◽  
...  
Keyword(s):  
Circuit Design ◽  
Calibration Method ◽  
Low Noise ◽  
Low Noise Amplifier ◽  
Self Calibration ◽  
Noise Amplifier

A Self-Calibration Method for Robotic Measurement System

1999 ◽  
Author(s):  
Chunhe Gong ◽  
Jingxia Yuan ◽  
Jun Ni
Keyword(s):  
Coordinate System ◽  
Measurement System ◽  
Calibration Method ◽  
Position Measurement ◽  
Robot Calibration ◽  
Robot System ◽  
Self Calibration ◽  
World Coordinate System ◽  
Robot Accuracy ◽  
Calibration Methods

Abstract Robot calibration plays an increasingly important role in manufacturing. For robot calibration on the manufacturing floor, it is desirable that the calibration technique be easy and convenient to implement. This paper presents a new self-calibration method to calibrate and compensate for robot system kinematic errors. Compared with the traditional calibration methods, this calibration method has several unique features. First, it is not necessary to apply an external measurement system to measure the robot end-effector position for the purpose of kinematic identification since the robot measurement system has a sensor as its integral part. Second, this self-calibration is based on distance measurement rather than absolute position measurement for kinematic identification; therefore the calibration of the transformation from the world coordinate system to the robot base coordinate system, known as base calibration, is not necessary. These features not only greatly facilitate the robot system calibration but also shorten the error propagation chain, therefore, increase the accuracy of parameter estimation. An integrated calibration system is designed to validate the effectiveness of this calibration method. Experimental results show that after calibration there is a significant improvement of robot accuracy over a typical robot workspace.

Obstacle detection based on depth fusion of lidar and radar in challenging conditions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Guotao Xie ◽  
Jing Zhang ◽  
Junfeng Tang ◽  
Hongfei Zhao ◽  
Ning Sun ◽  
...  
Keyword(s):  
False Alarm ◽  
Experimental Tests ◽  
Point Clouds ◽  
Calibration Method ◽  
Obstacle Detection ◽  
Environmental Perception ◽  
Fusion Model ◽  
Content Type ◽  
Self Calibration ◽  
Temporal Relationships

Purpose To the industrial application of intelligent and connected vehicles (ICVs), the robustness and accuracy of environmental perception are critical in challenging conditions. However, the accuracy of perception is closely related to the performance of sensors configured on the vehicle. To enhance sensors’ performance further to improve the accuracy of environmental perception, this paper aims to introduce an obstacle detection method based on the depth fusion of lidar and radar in challenging conditions, which could reduce the false rate resulting from sensors’ misdetection. Design/methodology/approach Firstly, a multi-layer self-calibration method is proposed based on the spatial and temporal relationships. Next, a depth fusion model is proposed to improve the performance of obstacle detection in challenging conditions. Finally, the study tests are carried out in challenging conditions, including straight unstructured road, unstructured road with rough surface and unstructured road with heavy dust or mist. Findings The experimental tests in challenging conditions demonstrate that the depth fusion model, comparing with the use of a single sensor, can filter out the false alarm of radar and point clouds of dust or mist received by lidar. So, the accuracy of objects detection is also improved under challenging conditions. Originality/value A multi-layer self-calibration method is conducive to improve the accuracy of the calibration and reduce the workload of manual calibration. Next, a depth fusion model based on lidar and radar can effectively get high precision by way of filtering out the false alarm of radar and point clouds of dust or mist received by lidar, which could improve ICVs’ performance in challenging conditions.

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