Gesture recognition method, device and computer-readable storage medium

    公开(公告)号:US12277801B2

    公开(公告)日:2025-04-15

    申请号:US17566734

    申请日:2021-12-31

    Abstract: A gesture recognition method includes: acquiring a target image containing a gesture to be recognized; inputting the target image to a gesture recognition model that has a first sub-model, a second sub-model, and a third sub-model, the first sub-model is to determine a gesture category and a gesture center point, the second sub-model is to determine an offset of the gesture center point, and the third sub-model is to determine a length and a width of a bounding box for the gesture to be recognized; acquiring an output result from the gesture recognition model, the output result includes the gesture category, the gesture center point, and the offset of the gesture center point, and the length and the width of the bounding box; and determining the gesture category and a position of the bounding box of the gesture to be recognized according to the output result.

    Pet feeder
    222.
    发明授权

    公开(公告)号:US12250929B2

    公开(公告)日:2025-03-18

    申请号:US18381181

    申请日:2023-10-18

    Abstract: A pet feeder includes: a housing, a heat conduction member, a temperature adjustment structure and a heat dissipation member that are arranged in the housing, a tray, a cover, and an actuating mechanism. The temperature adjustment structure includes a thermoelectric cooling member and a control module. The thermoelectric cooling member includes a first side connected to the heat conduction member and a second side in contact with the heat dissipation member. The control module is to control the first side of the thermoelectric cooling member to heat or cool. The tray is arranged in the housing and connected to the heat conduction member, and defines two compartments for placing pet food. The cover is arranged on the tray and defines a window in communication with the at least two compartments. The actuating mechanism is arranged in the housing and is to rotate the tray or the cover.

    Robot control method, robot, and computer-readable storage medium

    公开(公告)号:US12186909B2

    公开(公告)日:2025-01-07

    申请号:US18075450

    申请日:2022-12-06

    Abstract: A robot control method, a robot, and a computer-readable storage medium are provided. The method includes: obtaining a trajectory planning parameter of joint(s) of the robot, force data of an end of the robot, and force data of the joint(s); obtaining an end admittance compensation amount; determining a first joint parameter and a first slack variable corresponding to the end admittance compensation amount in a joint space of each of the joint(s) based on the end admittance compensation amount and the trajectory planning parameter; obtaining a joint admittance compensation amount; determining a second joint parameter based on the first joint parameter, the first slack variable, the joint admittance compensation amount, and the trajectory planning parameter; determining a target joint commanding position based on the second joint parameter; and controlling the robot to move according to the target joint commanding position.

    Litter device for pet
    224.
    发明授权

    公开(公告)号:US12171188B2

    公开(公告)日:2024-12-24

    申请号:US17887536

    申请日:2022-08-15

    Abstract: A pet litter device includes: a base configured to be placed on a support surface, the base defining a recessed portion that comprises a recess surface defining an opening, and a drum rotatably connected to the base and partly received in the recessed portion. The drum has an outer lateral surface. The recess surface and a portion of the outer lateral surface that faces the recess surface define a gap and form a passage in communication with the opening. The recess surface is to guide litter particles entering the passage to pass through the opening to fall on the support surface.

    METHOD FOR BINOCULAR DEPTH ESTIMATION, EMBEDDED DEVICE, AND READABLE STORAGE MEDIUM

    公开(公告)号:US20240331173A1

    公开(公告)日:2024-10-03

    申请号:US18603100

    申请日:2024-03-12

    CPC classification number: G06T7/50 G06V10/7715 G06V10/82 G06T2207/20228

    Abstract: A method for binocular depth estimation is provided, including: obtaining binocular images and performing feature extraction on the binocular images to obtain left and right feature mappings; performing disparity construction by using the left and right feature mappings to obtain a disparity cost volume with a reduced dimension; performing attention feature learning on the disparity cost volume to obtain an attention feature vector and performing feature weighting on the disparity cost volume by using the attention feature vector to obtain a weighted cost volume; performing disparity regression on the weighted cost volume based on a two-dimensional convolution to obtain a prediction disparity map; and performing disparity depth conversion on the prediction disparity map to obtain a depth map of the binocular images.

    METHOD FOR DETERMINING POSE OF ROBOT, ROBOT AND COMPUTER-READABLE STORAGE MEDIUM

    公开(公告)号:US20240286282A1

    公开(公告)日:2024-08-29

    申请号:US18395309

    申请日:2023-12-22

    CPC classification number: B25J9/1661 B25J9/161 B25J9/1653 B25J19/022

    Abstract: A method for determining a pose of a robot having a lidar including: obtaining a first pose of the robot in a map coordinate system; determining first positions of laser points corresponding to the lidar in the map coordinate system according to the first pose when the lidar performs laser scanning; determining matching scores between the first positions and grids where the first positions are located according to the first positions and mean values of the grids where the first positions are located, wherein the grids are grids in a probability map corresponding to the map coordinate system; determining a first confidence level for the first pose based on the matching scores; and determining a target pose according to the first confidence level.

    Electric wheelchair
    228.
    外观设计

    公开(公告)号:USD1038846S1

    公开(公告)日:2024-08-13

    申请号:US29897363

    申请日:2023-07-14

    Abstract: FIG. 1 is a first perspective view of an electric wheelchair showing the claimed design in accordance with the present disclosure;
    FIG. 2 is a second perspective view thereof;
    FIG. 3 is a front elevational view thereof;
    FIG. 4 is a rear elevational view thereof;
    FIG. 5 is a left side elevational view thereof;
    FIG. 6 is a right side elevational view thereof;
    FIG. 7 is a top plan view thereof; and,
    FIG. 8 is a bottom plan view thereof.
    The broken lines in the Figures are for the purpose of illustrating portions of the article that form no part of the claimed design.

    METHOD FOR ROBOT TELEOPERATION CONTROL, ROBOT, AND ELECTRONIC DEVICE

    公开(公告)号:US20240198532A1

    公开(公告)日:2024-06-20

    申请号:US18518960

    申请日:2023-11-25

    CPC classification number: B25J9/1689

    Abstract: A method for robot telcoperation control is provided. The method includes acquiring target action data and displacement data of a target object, wherein the target action data includes head action data and arm action data; controlling a target robot to act according to the target action data to enable the target robot to complete an action corresponding to the target action data; and performing centroid trajectory planning on the target robot based on a model predictive control (MPC) algorithm according to the displacement data to obtain a target centroid trajectory, and establishing a spring-damping system to track the target centroid trajectory so as to enable the target robot to move to a position corresponding to the displacement data.

    Motion control method, robot controller and computer readable storage medium

    公开(公告)号:US11938635B2

    公开(公告)日:2024-03-26

    申请号:US17702819

    申请日:2022-03-24

    CPC classification number: B25J9/1664 B25J9/1607

    Abstract: A motion control method, a robot controller, and a computer readable storage medium are provided. The method includes: calculating an inverse Jacobian matrix of a whole-body generalized coordinate vector at a current time relative to an actual task space vector of a humanoid robot; calculating a target generalized coordinate vector corresponding to a to-be-executed task space vector at a current moment by combining an actual task space vector and the to-be-executed task space vector into a null space of the inverse Jacobian matrix according to preset position constraint(s) corresponding to the whole-body generalized coordinate vector; and controlling a motion state of the humanoid robot according to the target generalized coordinate vector. In this manner, the motion of the humanoid robot is optimized as a whole to achieve the purpose of controlling the humanoid robot to avoid the limits of the motion of joints.

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