Domain adaptation for simulated motor backlash

    公开(公告)号:US12280499B2

    公开(公告)日:2025-04-22

    申请号:US17095586

    申请日:2020-11-11

    Abstract: A method, system and computer program product for training a control input system involve taking an integral of an output value from a Motion Decision Neural Network for one or more movable joints to generate an integrated output value and comparing the integrated output value to a backlash threshold. A subsequent output value is generated using a machine learning algorithm that includes a sensor value and a previous joint position if the integrated output value does not at least meet the threshold. A position of the one or more movable joints is simulated based on an integral of the subsequent output value; and the Motion Decision Neural Network is trained with the machine learning algorithm based upon at least a result of the simulation of the position of the one or more movable joints.

    Method for robotic training based on randomization of surface damping

    公开(公告)号:US12017359B2

    公开(公告)日:2024-06-25

    申请号:US17095640

    申请日:2020-11-11

    CPC classification number: B25J9/163 B25J9/12 G06F30/27 G06N3/084 G06N3/048

    Abstract: A method, system and computer product for training a control input system involve taking an integral of an output value from a Motion Decision Neural Network for one or more movable joints to generate an integrated output value and generating a subsequent output value using a machine learning algorithm that includes a sensor value and a previous joint position if the integrated output value does not at least meet the threshold. Surface damping interactions with at least a simulated environment, a rigid body position and a position of the one or more movable joints based on an integral of the subsequent output value are simulated. The Motion Decision Neural Network is trained with the machine learning algorithm based upon at least a result of the simulation of the simulated environment and position of the one or more movable joints.

    Event driven sensor (EDS) tracking of light emitting diode (LED) array

    公开(公告)号:US11340696B2

    公开(公告)日:2022-05-24

    申请号:US16741051

    申请日:2020-01-13

    Inventor: Sergey Bashkirov

    Abstract: An event driven sensor (EDS) is used for simultaneous localization and mapping (SLAM) and in particular is used in conjunction with a constellation of light emitting diodes (LED) to simultaneously localize all LEDs and track EDS pose in space. The EDS may be stationary or moveable and can track moveable LED constellations as rigid bodies. Each individual LED is distinguished at a high rate using minimal computational resources (no image processing). Thus, instead of a camera and image processing, rapidly pulsing LEDs detected by the EDS are used for feature points such that EDS events are related to only one LED at a time.

    VARIABLE MAGNETIC FIELD-BASED POSITION
    6.
    发明申请

    公开(公告)号:US20180193728A1

    公开(公告)日:2018-07-12

    申请号:US15402539

    申请日:2017-01-10

    CPC classification number: A63F13/21 A63F13/428

    Abstract: To derive three dimensional (3D) position and orientation of a 3-axis (or more) magnetometer/accelerometer device (such as may be implemented in VR or AR headset or computer game controller) without line of sight constraints, a spinning magnetic field is used to discriminate and remove the external (Earth's) magnetic field from the spinning magnetic field. This reduces the problem to finding the distance to the source of the magnetic field using a calibration table (or formula), finding two angles describing the deviation of the magnetic sensor from the axis of rotation of the spinning magnetic field and the phase around this axis, and from these values deriving the orientation of the sensor.

    EVENT DRIVEN SENSOR (EDS) TRACKING OF LIGHT EMITTING DIODE (LED) ARRAY

    公开(公告)号:US20240160279A1

    公开(公告)日:2024-05-16

    申请号:US18479995

    申请日:2023-10-03

    Inventor: Sergey Bashkirov

    CPC classification number: G06F3/012 G01S5/16 G06F3/0325

    Abstract: An event driven sensor (EDS) is used for simultaneous localization and mapping (SLAM) and in particular is used in conjunction with a constellation of light emitting diodes (LED) to simultaneously localize all LEDs and track EDS pose in space. The EDS may be stationary or moveable and can track moveable LED constellations as rigid bodies. Each individual LED is distinguished at a high rate using minimal computational resources (no image processing). Thus, instead of a camera and image processing, rapidly pulsing LEDs detected by the EDS are used for feature points such that EDS events are related to only one LED at a time.

    Disambiguation of poses
    8.
    发明授权

    公开(公告)号:US11763508B2

    公开(公告)日:2023-09-19

    申请号:US17095481

    申请日:2020-11-11

    Abstract: Computer animation involving pose disambiguation is disclosed. Two or more source segmentation masks are generated from corresponding contemporaneous video images of a character from different points of view. A three-dimensional model of an animation character corresponding to the character in the two or more contemporaneous video images is generated. Two or more different target segmentation masks corresponding to different views of the animation character corresponding to the character in the two or more video images. Each target segmentation mask is compared to a corresponding source segmentation mask from the comparison it is determined whether a pose of the three-dimensional model corresponds to a pose of the character in the video images. The model is used to generate a frame of animation of the animated character when the pose of model corresponds to the pose of the character in the video images.

    METHOD FOR ROBOTIC TRAINING BASED ON RANDOMIZATION OF SURFACE DAMPING

    公开(公告)号:US20220143822A1

    公开(公告)日:2022-05-12

    申请号:US17095640

    申请日:2020-11-11

    Abstract: A method, system and computer product for training a control input system involve taking an integral of an output value from a Motion Decision Neural Network for one or more movable joints to generate an integrated output value and generating a subsequent output value using a machine learning algorithm that includes a sensor value and a previous joint position if the integrated output value does not at least meet the threshold. Surface damping interactions with at least a simulated environment, a rigid body position and a position of the one or more movable joints based on an integral of the subsequent output value are simulated. The Motion Decision Neural Network is trained with the machine learning algorithm based upon at least a result of the simulation of the simulated environment and position of the one or more movable joints.

    METHOD FOR ROBOTIC TRAINING BASED ON RANDOMIZATION OF SURFACE STIFFNESS

    公开(公告)号:US20220143821A1

    公开(公告)日:2022-05-12

    申请号:US17095617

    申请日:2020-11-11

    Abstract: A method, system and computer product for training a control input system involve taking an integral of an output value from a Motion Decision Neural Network for one or more movable joints to generate an integrated output value and generating a subsequent output value using a machine learning algorithm that includes a sensor value and a previous joint position if the integrated output value does not at least meet the threshold. Surface stiffness interactions with at least a simulated environment, a rigid body position and a position of the one or more movable joints based on an integral of the subsequent output value are simulated. The Motion Decision Neural Network is trained with the machine learning algorithm based upon at least a result of the simulation of the simulated environment and position of the one or more movable joints.

Patent Agency Ranking