公开(公告)号：US20220317695A1

公开(公告)日：2022-10-06

申请号：US17309922

申请日：2020-09-10

Applicant: GOERTEK INC.

Inventor： Xueqiang WANG ,  Yifan ZHANG ,  Libing ZOU ,  Fuqiang ZHANG

IPC: G05D1/02 ,  G05D1/00 ,  G06N3/04 ,  G06N3/08 ,  G06N7/00

Abstract: A multi-AGV motion planning method, device and system are disclosed. The method of the present disclosure comprises: establishing an object model through reinforcement learning; building a neural network model based on the object model, performing environment settings including AGV group deployment, and using the object model of the AGV in a set environment to train the neural network model until a stable neural network model is obtained; setting an action constraint rule; and after the motion planning is started, inputting the state of current AGV, states of other AGVs and permitted actions in a current environment into the neural network model after trained, obtaining the evaluation indexes of a motion planning result output by the neural network model, obtaining an action to be executed of the current AGV according to the evaluation indexes, and performing validity judgment on the action to be executed using the action constraint rule.

公开(公告)号：US20220307859A1

公开(公告)日：2022-09-29

申请号：US17309926

申请日：2020-11-06

Applicant: GOERTEK INC.

Inventor： Libing ZOU ,  Yifan ZHANG ,  Fuqiang ZHANG ,  Baoming LI

IPC: G01C21/00 ,  G01C21/32

Abstract: The present application discloses a method and device for updating a map. The method for updating a map according to the present embodiment includes: in a process of movement of a robot, when it is detected that an actual environment is different from an environment that is indicated by a global map that has already been established, starting up map updating, and establishing an initial local map; determining a locating point according to acquired sensor data and the global map, and optimizing the initial local map according to the locating point, to obtain an optimized local map; and covering a corresponding area of the global map by using the optimized local map, to complete updating of the global map. The embodiments of the present application improve the locating accuracy, ensure the speed and efficiency of the map updating, and save time.

公开(公告)号：US20220172337A1

公开(公告)日：2022-06-02

申请号：US17594142

申请日：2020-10-30

Applicant: GOERTEK INC.

Inventor： Shiyu LI ,  Yifan ZHANG ,  Jifeng TIAN

IPC: G06T7/00 ,  G06V30/14 ,  G06T7/90 ,  G06T11/00 ,  G06T3/00

Abstract: A character defect detection method and device are disclosed. The character defect detection method comprises: acquiring an image to be inspected containing a character and a template character image corresponding to the character, and converting the image to be inspected into an image having a format consistent with a format of the template character image; extracting a first valid area containing the character from the image to be inspected, and extracting a second valid area containing a template character from the template character image; obtaining a first image based on the first valid area, and obtaining a second image based on the second valid area; calculating a transformed image indicating an information difference between the first image and the second image based on the first image and the second image; and obtaining a character defect detection result of the image to be inspected based on information of the transformed image.

公开(公告)号：US20210374940A1

公开(公告)日：2021-12-02

申请号：US17250262

申请日：2020-08-29

Applicant: GOERTEK INC.

Inventor： Jie LIU ,  Jifeng TIAN ,  Wenchao ZHANG ,  Yifan ZHANG

IPC: G06T7/00 ,  G06K9/62

Abstract: A product defect detection method, device and system are disclosed. The method comprises: constructing a defect detection framework including segmentation networks, a concatenating network and a classification network, and setting a quantity of the segmentation network according to product defect types, wherein each segmentation network corresponds to a defect type; concatenating the sample image with the mask image output by each segmentation network by using the concatenating network to obtain a concatenated image; training the classification network by using the concatenated images to obtain a classification network capable of correctly identifying a product defect and a defect type; and when performing product defect detection, inputting a product image acquired into the defect detection framework, and detecting a product defect and a defect type existing in the product by using the segmentation networks, the concatenating network and the classification network.

公开(公告)号：US20220309764A1

公开(公告)日：2022-09-29

申请号：US17275800

申请日：2020-08-26

Applicant: GOERTEK INC.

Inventor： Jie LIU ,  Jifeng TIAN ,  Fuli XIE ,  Shunran DI ,  Yifan ZHANG

IPC: G06V10/764 ,  G06V10/82 ,  G06V10/26 ,  G06N3/08

Abstract: A method and device for small sample defect classification and a computing equipment are disclosed. The method comprises: separating a target to be tested into parts, and segmenting an original image of the target to be tested into at least two sub-images containing different parts according to the separated parts; establishing small sample classification models with respect to each sub-image and the original image respectively, and obtaining a classification result of each sub-image and a classification result of the original image by using corresponding classification models, wherein the classification result includes a defect category and a corresponding category probability; and determining and outputting a defect category of the target to be tested according to classification results of all the sub-images and the original image.

公开(公告)号：US20220171512A1

公开(公告)日：2022-06-02

申请号：US17594145

申请日：2020-10-30

Applicant: GOERTEK INC.

Inventor： Libing ZOU ,  Yifan ZHANG ,  Fuqiang ZHANG ,  Xueqiang WANG

IPC: G06F3/0487 ,  G06F3/14 ,  G06V40/16 ,  G06V40/18 ,  G06V10/82 ,  G06F3/0354 ,  G06F3/038 ,  G06F3/01

Abstract: A multi-screen display system and a mouse switching control method are disclosed. The mouse switching control method is applied to a multi-screen display system comprising a main display screen and at least one extended display screen, and comprises: obtaining user images collected by cameras installed on the main display screen and the extended display screen respectively; inputting the user images into a neural network model, and predicting a screen that a user is currently paying attention to using the neural network model to obtain a prediction result; and controlling to switch a mouse to the screen that a user is currently paying attention to according to the prediction result. The system and mouse switching control method are based on self-learning of visual attention, predict the current screen operated by the user, automatically switch the mouse to the corresponding screen position, and improve the user experience.

公开(公告)号：US20190209050A1

公开(公告)日：2019-07-11

申请号：US16327173

申请日：2017-07-13

Applicant: Goertek Inc.

Inventor： Pengcheng SU ,  Yifan ZHANG

IPC: A61B5/11 ,  A61B5/00 ,  A63B24/00

CPC classification number: A61B5/1123 ,  A61B5/11 ,  A61B5/1121 ,  A61B5/7246 ,  A61B5/7267 ,  A61B2503/10 ,  A61B2562/0219 ,  A63B24/0062 ,  A63B71/06 ,  A63B2024/0068 ,  A63B2220/44 ,  A63B2220/836 ,  A63B2244/20

Abstract: A wearable device and a method for monitoring a movement state by using the same are disclosed. A sensor is provided in the wearable device. The method comprises: controlling the sensor to collect movement data of a user when a monitoring process starts; extracting one or more features for identifying the movement state of the user from the movement data to obtain test data; and matching the test data with stored template data representing predetermined movement states, to obtain template data that successfully match the test data, and determining occurrence of a movement state corresponding to the matched template data associated with the test data.

公开(公告)号：US20230402949A1

公开(公告)日：2023-12-14

申请号：US18449141

申请日：2023-08-14

Applicant: GOERTEK INC.

Inventor： Yifan ZHANG ,  Pengbo Feng ,  Xueqiang Wang ,  Tao Han

IPC: H02P25/034 ,  H02P7/025

CPC classification number: H02P25/034 ,  H02P7/025

Abstract: Disclosed are a voice coil motor, a method and a device for controlling the voice coil motor. The voice coil motor includes an outer coil module and an inner coil module inside the outer coil module, an air gap for the inner coil module to move is formed between the inner coil module and the outer coil module. The method includes: driving the outer coil module to generate an outer coil electromagnetic force; determining an inner coil current instruction according to an expectation force instruction and force feedback information sent by an executing mechanism of the voice coil motor; driving the inner coil module of the voice coil motor to generate an inner coil electromagnetic force according to the inner coil current instruction; and enabling the executing mechanism to generate a motor acting force according to the outer coil electromagnetic force and the inner coil electromagnetic force.

公开(公告)号：US20220309765A1

公开(公告)日：2022-09-29

申请号：US17309308

申请日：2020-10-30

Applicant: GOERTEK INC.

Inventor： Shunran DI ,  Yifan ZHANG ,  Jie LIU ,  Jifeng TIAN

IPC: G06V10/764 ,  G06V10/771 ,  G06V10/776 ,  G06V10/82 ,  G06N3/08

Abstract: The present disclosure discloses a method and device for optimizing an object-class model based on a neural network. The method includes: establishing the object-class model based on the neural network, training the object-class model, and realizing classification of target images by using the object-class model that has been trained; and when a new target image is generated, and the new target image is an image corresponding to a new condition of a target and is capable of still being classified into an original classification system, judging a result of identification of the object-class model to the new target image, and if the object-class model is not capable of correctly classifying the new target image, according to the new target image, selecting some of parameters, adjusting the some of parameters, and training to obtain an object-class model that is capable of correctly classifying the new target image.

公开(公告)号：US20220309640A1

公开(公告)日：2022-09-29

申请号：US17309407

申请日：2020-08-26

Applicant: GOERTEK INC.

Inventor： Jie LIU ,  Jifeng TIAN ,  Fuli XIE ,  Shunran DI ,  Yifan ZHANG

IPC: G06T7/00 ,  G06V10/70 ,  G01N21/88

Abstract: A product defect detection method, device and system are disclosed. The method comprises: acquiring a sample image of a product, extracting candidate image blocks probably including a product defect from the sample image, and extracting preset shape features corresponding to the candidate image blocks and texture features corresponding to the candidate image blocks; training a first-level classifier using the preset shape features to obtain a first-level classifier that can further screen out target image blocks probably including a product defect from the candidate image blocks; training a second-level classifier using the texture features to obtain a second-level classifier that can correctly identify a product defect; and when performing product defect detection, inputting preset shape features of candidate image blocks extracted from a product image into the first-level classifier, and then inputting texture features of obtained target image blocks into the second-level classifier to detect a defect in the product.