LIGHTWEIGHT HAND EXOSKELETON FORCE FEEDBACK APPARATUS

    公开(公告)号:US20250076981A1

    公开(公告)日:2025-03-06

    申请号:US18634995

    申请日:2024-04-14

    Abstract: Disclosed is a lightweight hand exoskeleton force feedback apparatus, including a driver, a first rotating link, a second rotating link, a first linkage link, a second linkage link, a finger sleeve, and a pressure sensor fixing member; the driver is worn on a back of metacarpal bone of a human hand, the finger sleeve is fixed on an index finger, and the pressure sensor fixing member is fixed below the index finger; when the human hand bends to simulate a state of grasping an object, the driver drives the first rotating link to couple with the first linkage link and the second linkage link through the second rotating link to drive the finger sleeve to bend and stretch, force feedback is applied to the fingertip, and a pressure is accordingly imposed on a pressure sensor of the pressure sensor fixing member, so that closed-loop force feedback control is implemented.

    COMBINED SIX-DIMENSIONAL FORCE SENSOR BASED ON THIN-FILM SPUTTERING TECHNOLOGY

    公开(公告)号:US20240328872A1

    公开(公告)日:2024-10-03

    申请号:US18649980

    申请日:2024-04-29

    CPC classification number: G01L1/2206 G01L1/205

    Abstract: A combined six-dimensional force sensor based on thin-film sputtering technology includes a force transmission table, a cross beam, a base, a top cover, a bottom cover and strain gauges. Strain gauges are sputtered on the elastomer structure to form six sets of Wheatstone bridges. The measurement method of the six-dimensional force sensor is that: an input force/moment of a certain dimension acts on the elastomer structure including the force transmission table and the cross beam through the top cover, the cross beam is deformed and resistance values of strain gauges at corresponding positions change, and output voltages of corresponding bridges change.

    PIPELINE PATROL INSPECTION ROBOT HAVING VARIABLE TRACKS AND CONTROL METHOD THEREFOR

    公开(公告)号:US20220373122A1

    公开(公告)日:2022-11-24

    申请号:US17635967

    申请日:2021-01-04

    Abstract: The present invention discloses a pipeline patrol inspection robot having variable tracks and a control method therefor. The pipeline patrol inspection robot of the present invention includes a robot body, track assemblies symmetrically disposed on a left side and a right side of the robot body, and a movement driving mechanism. The robot body is connected to the track assemblies on the left side and the right side by track fixtures, and track angle adjusting mechanisms are respectively connected between the robot body and the track assemblies on the left side and the right side. By means of the present invention, a track camber angle can be adjusted. In addition, each track angle adjusting mechanism is independent, and has desirable flexibility to adapt to different pipeline environments.

    TWO-DEGREE-OF-FREEDOM ROPE-DRIVEN FINGER FORCE FEEDBACK DEVICE

    公开(公告)号:US20220314458A1

    公开(公告)日:2022-10-06

    申请号:US17609446

    申请日:2021-01-29

    Abstract: The present invention provides a two-degree-of-freedom rope-driven finger force feedback device. The two-degree-of-freedom rope-driven finger force feedback device includes a hand support mechanism, a thumb movement mechanism, an index finger movement mechanism, and a handle mechanism. The hand support mechanism includes a motor, a motor shaft sleeve, a sliding rail, and an inertial measurement unit (IMU) sensor. The thumb movement mechanism includes a long rotary disc, a torque sensor, an angle sensor, a thumb sleeve, a pressure sensor, two links, a thumb brace, and a thumb fixing ring. The handle mechanism includes a cylindrical handle, a pressure sensor, a flexible fixing band, and a slider. Torque is driven between the rotary disc and the motor by using a rope. The handle mechanism is movable forward and backward and is capable of automatic restoration. By means of the present invention, the problems of the high costs of a conventional finger force feedback device and the unadjustable characteristic of the conventional finger force feedback device are overcome. The device can be tightly worn and has a self-adaptive degree of freedom. Rope driving can ensure a gentle, smooth, and real feedback force. By means of the mounted sensors, information such as a hand posture, a rotation angle and a grip force of a thumb and an index finger, and a contact force of a middle finger can be transmitted in real time.

    PALM-SUPPORTED FINGER REHABILITATION TRAINING DEVICE AND APPLICATION METHOD THEREOF

    公开(公告)号:US20210401657A1

    公开(公告)日:2021-12-30

    申请号:US17293448

    申请日:2019-03-21

    Abstract: A palm-supported finger rehabilitation training device comprises a mounting base, a finger rehabilitation training mechanism mounted on the mounting base, and a driving mechanism for driving the finger rehabilitation training mechanism; wherein the finger rehabilitation training mechanism comprises four independent and structurally identical combined transmission devices for finger training corresponding to a forefinger, a middle finger, a ring finger and a little finger of a human hand, respectively, and the mounting base is provided with a supporting surface capable of supporting a human palm; wherein each combined transmission device for finger training comprises an MP movable chute, a PIP fingerstall, a DIP fingerstall and a connecting rod transmission mechanism; a force sensor is provided to acquire force feedback information to determine and control force stability, and a space sensor is provided to acquire space angle information to control space positions of fingers in real time.

    METHOD FOR IDENTIFYING SKILLS OF HUMAN-MACHINE COOPERATION ROBOT BASED ON GENERATIVE ADVERSARIAL IMITATION LEARNING

    公开(公告)号:US20240359320A1

    公开(公告)日:2024-10-31

    申请号:US18246860

    申请日:2022-08-12

    CPC classification number: B25J9/163

    Abstract: Disclosed in the present disclosure is a method for identifying skills of a human-machine cooperation robot based on a generative adversarial imitation learning, which includes: firstly, defining classifications of human-machine cooperation skills that needed to be conducted; conducing demonstrations on different classifications of the skills by human experts, and collecting image information and data in the demonstrations to make calibrations; identifying the image information by means of image processing, extracting effective feature vectors capable of clearly distinguishing the different classifications of the skills and taking the effective feature vectors as demonstration teaching data; training a plurality of discriminators respectively by utilizing the acquired demonstration teaching data through a method of the generative adversarial imitation learning; extracting user's data after the training and putting the data into different discriminators, and taking a discriminator corresponding to a maximum value eventually output as an output result of identifying the skills. The present disclosure innovatively combines a computer image recognition with the famous generative adversarial imitation learning in a imitation learning, which has short training time and high learning efficiencies.

    MULTI-DEGREE-OF-FREEDOM MYOELECTRIC ARTIFICIAL HAND CONTROL SYSTEM AND METHOD FOR USING SAME

    公开(公告)号:US20220355469A1

    公开(公告)日:2022-11-10

    申请号:US17628753

    申请日:2020-06-03

    Abstract: Provided are a multi-degree-of-freedom myoelectric artificial hand control system and a method for using same. The system comprises a robotic hand, a robotic wrist (2), a stump receiving cavity (1) and a data processor (3), wherein the robotic hand and the stump receiving cavity (1) are respectively mounted on two ends of the robotic wrist (2); a multi-channel myoelectric array electrode oversleeve, a control unit circuit board, and a battery are connected in the stump receiving cavity (1); and the other end of the control unit circuit board is connected to the robotic hand and the robotic wrist (2). The method for using the system comprises the following steps: (S1) a user wearing a multi-channel myoelectric array electrode oversleeve, and connecting a battery and a control unit circuit board; (S2) the user completing a gesture, collecting a surface electromyography signal and then uploading same to a data processor (3); (S3) the data processor (3) receiving the surface electromyography signal and inputting same into a neural network algorithm to generate a gesture prediction model; and (S4) the user controlling the multi-degree-of-freedom movement of the robotic wrist (2) and the robotic hand. By means of the system, continuous gestures and the gesture strength thereof can be identified, and multi-degree-of-freedom gestures can be made.

    METHOD FOR REDUCING THE HYSTERESIS ERROR AND THE HIGH FREQUENCY NOISE ERROR OF CAPACITIVE TACTILE SENSORS

    公开(公告)号:US20220107237A1

    公开(公告)日:2022-04-07

    申请号:US17288534

    申请日:2020-07-01

    Abstract: A method for reducing hysteresis error and high frequency noise error of capacitive tactile sensors includes the following steps: step 1: calibration, specifically including positive stroke calibration to form n positive stroke curves and negative stroke calibration to form n negative stroke curves; step 2: averaging, specifically including positive stroke averaging to form an average positive stroke curve, negative stroke averaging to form an average negative stroke curve, and comprehensive averaging to form a comprehensive stroke curve; step 3: fitting modeling, to obtain a positive stroke fitting function, a negative stroke fitting function, and a comprehensive fitting function; step 4: measurement; step 5: noise filtering; step 6: stroke direction discrimination; and step 7: resolving, to obtain the force at the current time by using a corresponding fitting function based on the stroke direction discrimination result.

    NATURAL HUMAN-COMPUTER INTERACTION SYSTEM BASED ON MULTI-SENSING DATA FUSION

    公开(公告)号:US20210132681A1

    公开(公告)日:2021-05-06

    申请号:US16475384

    申请日:2018-05-23

    Abstract: A natural human-computer interaction system based on multi-sensing data fusion comprises a MEMS anti tracking device, a visual tracking device, a force feedback device and a PC terminal. The MEMS aim tracking device is composed of three sets of independent MEMS sensors for collecting arm joint angle information and measuring an arm motion trajectory. The visual tracking device is composed of a binocular camera for collecting image information and measuring a finger motion trajectory. The force feedback device is mounted in a palm of an operator for providing a feedback force to the finger. The PC terminal comprises a data display module, an arm motion calculating module, an image processing module, a mechanics calculating module and a virtual scene rendering module. The system tracks the arm motion trajectory of the operator by taking and tracks the finger motion trajectory of the operator and provides force feedback interaction to the finger of the operator.

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