公开(公告)号：US11969904B2

公开(公告)日：2024-04-30

申请号：US17417416

申请日：2020-03-24

Applicant: QINGDAO TECHNOLOGICAL UNIVERSITY

Inventor： Cheng Jun Chen ,  Xu Tong Ding ,  Yong Pan ,  Dong Nian Li ,  Jun Hong

IPC: B25J9/16 ,  B25J9/02

CPC classification number: B25J9/1697 ,  B25J9/023 ,  B25J9/163 ,  B25J9/1653

Abstract: A registration system for robot-oriented augmented reality teaching system, comprising: a physical robot unit, a registration unit, a virtual robot generation unit and a computer; the physical robot unit comprising a physical robot, a physical robot controller and a robot point-to-point intermittent movement control program; the physical robot provided thereon with a physical robot base coordinate system; the physical robot controller connected with the physical robot and the computer respectively; the robot point-to-point intermittent movement control program installed in the computer; the registration unit comprising a registration marker, a camera and a conversion calculation unit; the registration marker arranged on the physical robot body; the camera fixed in a physical environment except the physical robot; the camera connected with the computer, and the conversion calculation unit arranged in the computer; the virtual robot generation unit arranged in the computer and used for generating a virtual robot model.

公开(公告)号：US11645827B2

公开(公告)日：2023-05-09

申请号：US17345122

申请日：2021-06-11

Applicant: QINGDAO TECHNOLOGICAL UNIVERSITY

Inventor： Cheng Jun Chen ,  Yao Shuai Yue ,  Dong Nian Li ,  Jun Hong

IPC: G06T7/00 ,  G06F18/23213 ,  G06V10/44

CPC classification number: G06V10/443 ,  G06F18/23213 ,  G06T7/0004

Abstract: The present invention relates to a detection method for an assembly body multi-view change based on feature matching, comprising the following steps: S1, acquiring a first image and a second image; S2, performing feature point extraction and feature matching on the first image and the second image to obtain a matching pair set, a first unmatched point set of the first image and a second unmatched point set of the second image; S3, acquiring a first to-be-matched area set of the first image according to the first unmatched point set; acquiring a second to-be-matched area set of the second image according to the second unmatched point set; S4, performing feature matching on each first unmatched area and each second unmatched area one by one to obtain a plurality of matching results; and S5, outputting the assembly body change type according to the plurality of matching results.

公开(公告)号：US11630972B2

公开(公告)日：2023-04-18

申请号：US17342592

申请日：2021-06-09

Applicant: QINGDAO TECHNOLOGICAL UNIVERSITY

Inventor： Cheng Jun Chen ,  Chang Zhi Li ,  Dong Nian Li ,  Jun Hong

IPC: G06K9/62 ,  G06V20/64

Abstract: An assembly change detection method based on attention mechanism, including: establishing a three-dimensional model of an assembly body, adding a tag to each part in the three-dimensional model, setting several assembly nodes, obtaining depth images of the three-dimensional model under each assembly node in different viewing angles, and obtaining a change tag image of a added part at each assembly node; selecting two depth images at front and back moments in different viewing angles as training samples; performing semantic fusion, feature extraction, attention mechanism processing and metric learning sequentially on the training samples, training a detection model, continuously selecting training samples to train the detection model, saving model parameters with optimal similarity during training, completing training; and obtaining depth images of successive assembly nodes during assembling the assembly body, inputting depth images into trained detection model, and outputting change image of added part of the assembly body during assembly.

公开(公告)号：US11971319B2

公开(公告)日：2024-04-30

申请号：US17279639

申请日：2020-05-07

Applicant: QINGDAO TECHNOLOGICAL UNIVERSITY ,  XI'AN JIAOTONG UNIVERSITY

Inventor： Cheng Jun Chen ,  Kai Huang ,  Dong Nian Li ,  Shuai Zheng ,  Jun Hong

IPC: G01L3/02 ,  A61B5/00 ,  A61B5/389 ,  G01L5/24 ,  G06T11/20

CPC classification number: G01L5/24 ,  A61B5/389 ,  A61B5/6824 ,  A61B5/6831 ,  A61B5/7264 ,  G06T11/206

Abstract: A surface electromyography signal-torque matching method based on multi-segmentation parallel CNN model (MSP-CNN model), step 1: collecting torque signals and surface electromyography (sEMG) signals when tightening a bolt; step 2: dividing a range of a transducer by at least two granularities, generating a plurality of torque sub-ranges corresponding to the at least two granularities and labeling the plurality of torque sub-ranges with torque labels; step 3: generating sEMG graphs of the sEMG signals in each time window; step 4: determining the torque labels of each time window under each of the at least two granularities according to the torque sub-ranges that average values of torques fall in; step 5: establishing a sample set; step 6: building a MSP-CNN model, and training parallel independent CNN models with sample datasets; and step 7: inputting the sEMG signals of the operator during assembly into trained MSP-CNN model and identifying assembly torques.