Research on the Pose Detection and Control Methods of Robot with Series-Parallel Structure

Yang, Dong; Li, Tie Jun; Liu, Jin Yue; Zhao, Hai Wen

doi:10.4028/www.scientific.net/amm.303-306.1685

Cited by 3 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At present, laser ranging sensors also play an important role in the field of civil engineering [21,22]. A laser ranging sensor first emits a laser pulse from its laser diode towards the target.…”

Section: (4) Other Parametersmentioning

confidence: 99%

Developing an Intelligent Monitoring Technology for Airport Stone Column Machines

Tang

Yuan

et al. 2020

Sensors

View full text Add to dashboard Cite

Most of the construction machinery for vibro-sinking stone columns, which are widely used in China, needs to be improved in terms of degree of automation. Engineering quality control is mainly carried out post-inspection; consequently, it is difficult to control the construction quality in real time. According to the construction characteristics of traditional stone column machines, we established the theory and model for the real-time monitoring of stone column construction, as well as put forward an intelligent monitoring method for stone column machines. With the comprehensive application of critical technologies such as the Global Navigation Satellite System (GNSS) measurement technology, laser ranging sensors, and massive data processing, an intelligent data acquisition technique and associated monitoring equipment for stone column construction machines are developed. The data acquisition and storage of crucial construction parameters, such as pile depth, pile point co-ordinates, bearing layer current, and reverse insertion times, are realized. A large number of actual construction data are collected and the construction quality parameters of stone column machines are obtained. By comparison with third-party detection data, it is verified that the intelligent monitoring technique for stone column machines proposed in this paper is feasible.

show abstract

Section: (4) Other Parametersmentioning

confidence: 99%

Developing an Intelligent Monitoring Technology for Airport Stone Column Machines

Tang

Yuan

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…However, the pose detection of end-effector for parallel robot is still difficult for the factors of the expensive detection equipment, the complex detection method, and the limited detection range. 2,3 Currently, the detection methods mainly include appending measuring robot, locating by dual-frequency interferometer, multisensors, and machine vision. [4][5][6] Compared with other methods, machine vision has the advantages of noncontact, powerful adaptability, high cost performance, and so on.…”

Section: Introductionmentioning

confidence: 99%

Pose detection of parallel robot based on improved RANSAC algorithm

Gao

Zhang

2019

Measurement and Control

View full text Add to dashboard Cite

For the factors of complex image background, unobvious end-effector characteristics and uneven illumination in the pose detection of parallel robot based on binocular vision, the detection speed, and accuracy cannot meet the requirement of the closed-loop control. So a pose detection method based on improved RANSAC algorithm is presented. First, considering that the image of parallel robot is rigid and has multiple corner points, the Harris–Scale Invariant Feature Transform algorithm is adopted to realize image prematching. The feature points are extracted by Harris and matched by Scale Invariant Feature Transform to realize good accuracy and real-time performance. Second, for the mismatching from prematching, an improved RANSAC algorithm is proposed to refine the prematching results. This improved algorithm can overcome the disadvantages of mismatching and time-consuming of the conventional RANSAC algorithm by selecting feature points in separated grids of the images and predetecting to validate provisional model. The improved RANSAC algorithm was applied to a self-developed novel 3-degrees of freedom parallel robot to verify the validity. The experiment results show that, compared with the conventional algorithm, the average matching time decreases by 63.45%, the average matching accuracy increases by 15.66%, the average deviations of pose detection in Y direction, Z direction, and roll angle [Formula: see text] decrease by 0.871 mm, 0.82 mm, and 0.704°, respectively, using improved algorithm to refine the prematching results. The real-time performance and accuracy of pose detection of parallel robot can be improved.

show abstract

Monocular Vision-Based Parameter Estimation for Mobile Robotic Painting

Zhao

Lü

et al. 2019

IEEE Trans. Instrum. Meas.

View full text Add to dashboard Cite

Research on the Pose Detection and Control Methods of Robot with Series-Parallel Structure

Cited by 3 publications

References 8 publications

Developing an Intelligent Monitoring Technology for Airport Stone Column Machines

Developing an Intelligent Monitoring Technology for Airport Stone Column Machines

Pose detection of parallel robot based on improved RANSAC algorithm

Monocular Vision-Based Parameter Estimation for Mobile Robotic Painting

Contact Info

Product

Resources

About