Electrostatic adsorption clutch force feedback data glove based on teleoperation system and design method thereof

Abstract

The invention provides an electrostatic adsorption clutch force feedback data glove based on a teleoperation system and a design method thereof, and belongs to the field of intelligent robots. Firstly, a hardware system of the output feedback data glove is designed based on inertial sensors, a system on a full programmable chip and an electrostatic adsorption clutch, the designed glove is worn on a human hand, and the inertial sensors arranged at the two ends of a joint are used for capturing the hand posture to obtain the bending angle of the human finger joint; an isomorphic finger joint motion mapping algorithm is adopted to convert into joint angle information of the slave manipulator, motion mapping of the master manipulator and the slave manipulator is achieved, then a force signal fed back by the slave manipulator is converted into kinesthetic force which can be sensed by the master manipulator through an electrostatic adsorption clutch, and master-slave force feedback is achieved.

Description

Technical Field

[0001] The invention belongs to the field of intelligent robots, and in particular relates to an electrostatic adsorption clutch force feedback data glove based on a teleoperation system and a design method thereof. Background Art

[0002] Robots can be used as pioneers of human exploration and platforms for humans to "contact" unknown environments. However, due to the limitations of key technologies such as artificial intelligence, mechanisms, control, and sensing, it is still unrealistic to develop intelligent robots that can complete tasks completely autonomously in unknown or changing environments. Therefore, people hope to combine human wisdom with robot intelligence, so that people can remotely control robots to operate objects in environments such as suffocation, strong radiation, high pressure and high temperature that are difficult for humans to approach, complete relatively complex remote operations, and give full play to the decision-making role of human intelligence and the execution ability of robots. The robot's end effector directly affects the robot's operating ability and intelligence level. The humanoid dexterous hand can be regarded as a group of intelligent machines installed on the robot arm that can realize flexible operation. Through the coordination of multiple fingers, it can maintain multi-point contact with the object during the grasping operation. In theory, it can grasp objects of any shape and apply operations and forces in any direction to the object, thereby completing high-precision and high-reliability grasping of objects of complex shapes without changing the end effector.

[0003] Although humans mainly obtain information through vision, it is difficult for the master operator to guide the slave robot to complete some relatively complex tasks if they rely solely on visual information. Combining visual and force information for remote operation can greatly improve the accuracy of control, and add the operator's feelings and decisions into it. The force reproduction device of the force feedback data glove transmits the force of the environment to the operator, so that he can feel that he is in it, and restore the real working scene to the greatest extent. This can greatly improve the on-site perception ability of the slave robot. Combining the on-site operation of the slave robot with the operator's decision can perform various complex tasks more efficiently and accurately. The force feedback data glove is the core of the force telepresence robot system, playing the dual role of force feedback and force control. It accurately converts the operator's operation and control intention into control instructions for controlling the remote robot, and realistically reproduces the force state of the slave's dexterous hand.

[0004] The invention with the authorization announcement number CN111645093B proposes a force feedback data glove for a teleoperation system. By wearing the designed glove on a human hand, the bending sensor on the back of the finger is used to capture the curvature of the human finger, and the fingertip mapping algorithm is used to convert the collected finger bending information into the joint angle information of the slave manipulator through the change of forward and inverse kinematics, so as to realize the motion mapping of the master and slave hands. The invention realizes force feedback through a micro cylinder, and measures the bending angle of each finger joint of the human hand in real time through the bending sensor on the back of the finger. The current design can only measure the bending angle of the finger joint, but cannot measure the yaw angle of the fingertip during the movement. This lack leads to certain errors in the motion mapping process, thereby affecting the accuracy of the overall system. Due to the lack of fingertip yaw angle measurement, the kinematic force feedback accuracy of the system is limited. In practical applications, this may cause the manipulator to perform poorly when performing complex tasks, and may even cause misoperation. In order to improve the accuracy and performance of the system, the present invention proposes an electrostatic adsorption clutch force feedback data glove based on a teleoperation system, an operation method and a system. Summary of the invention

[0005] The purpose of the present invention is to overcome the problem that the existing force feedback data gloves cannot measure the yaw angle of the fingertips during movement, resulting in certain errors in the motion mapping process, thereby affecting the accuracy of the overall system. Provided is an electrostatic adsorption clutch force feedback data glove based on a teleoperation system and a design method thereof.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: The electrostatic adsorption clutch force feedback data glove based on the teleoperation system includes a hand posture capture part and a kinesthetic force feedback part; The hand gesture capture part includes: a glove main body, a crystal gyroscope is arranged on the fingertips, a sensor stacking structure is arranged on the fingers, an FPC soft board is fixed on the fingers through a Velcro strap, an inertial sensor is welded on the FPC soft board, and a first integrated PCB board is fixed on the back of the hand, and the first integrated PCB board includes a gesture capture module; The kinesthetic force feedback part includes: an electrostatic adsorption clutch, a hand back guide rail is fixed on the hand back, a fixed electrode and a moving electrode are arranged on the hand back guide rail, the tail end of the moving electrode is fixed to the hand back guide rail through an elastic rope, the front end of the moving electrode is connected to a tension sensor, and is fixedly connected to the fingertip cover through a steel wire rope passing through the sleeve guide rail, and a second integrated PCB board is fixed on the forearm wearing the glove; The integrated PCB board uses the fully programmable system on chip ZYNQ, and the inertial sensor is a nine-axis IMU sensor.

[0007] The fully programmable system-on-chip ZYNQ consists of two parts, including a processing system PS and a programmable logic PL. The hand gesture capture part uses the programmable logic PL end, and the kinesthetic force feedback part uses the processing system PS end.

[0008] The sensor stack structure includes an angle sensor, an accelerometer, a gyroscope and a magnetometer. The posture fusion solution is performed through the data of the sensor stack structure to obtain the posture of the object to which the angle sensor is attached, and the movement angle of the joint is calculated in combination with the finger joint posture.

[0009] The operation method is as follows: Assemble the data glove: fix the hand rail on the back of the hand, stick the fixed electrode on the hand rail, install the fingertip cover on the fingertip, connect the fingertip cover, sleeve rail, tension sensor and motion electrode to form a transmission mechanism, fix the second integrated PCB board on the forearm, connect the fixed electrode and the motion electrode through wires to drive the data glove to follow the movement of the human hand; fix the FPC soft board on the finger through Velcro cable ties, fix the first integrated PCB board on the back of the glove, and connect the various parts through wires; The posture capture module is used to capture the postures of all joints of the human hand in real time. The inertial sensors fixed at both ends of each finger joint capture the bending angle of the joint, and the crystal gyroscope fixed at the fingertips captures the yaw angle of each finger MCP joint. The master-slave isomorphic joint mapping algorithm is then used to convert the angle information of each joint of the slave manipulator, and the motion mapping from the master hand to the slave hand is realized through the communication link. The feedback force of the slave-end manipulator is obtained, transmitted to the force feedback glove at the master-end through master-slave communication, and converted into the master hand feedback force through the master-slave force mapping algorithm; the feedback force is converted into a voltage value of the two input electrodes through the electrostatic adsorption clutch system, and the accurate voltage value is obtained through the master-end force feedback system, and kinesthetic force feedback is achieved by hindering finger movement.

[0010] The master-slave isomorphic joint mapping algorithm uses a solution algorithm that avoids singularity solution failure and a fingertip mapping algorithm with higher accuracy to complete the motion mapping from the master hand to the slave hand.

[0011] It includes a master-end system, a master-slave communication system and a slave-end system, wherein the master-end system includes a force feedback data glove and a master-end control system, which are used to measure the data of each joint angle of the human hand in real time, sample and process the signals of each sensor, and obtain the posture and movement information of the user's hand by solving the posture data by computer; the slave-end system receives the remote operation system command transmitted by the master-end system, and feeds back the information in the slave-end system to the master-end system; the master-slave communication system is used to realize the communication between the master-end system and the slave-end system.

[0012] It includes a synchronous calibration mechanical board and a synchronous calibration software system, which are used to calibrate each sensor.

[0013] The operation process of the system is as follows: Collect the movement of human hands; The motion mapping of the master hand is completed on the slave manipulator through the master-slave isomorphic joint mapping algorithm; The slave end manipulator contacts the environment to generate contact force; The slave manipulator senses the feedback force signal of the environmental contact force and transmits the feedback force signal to the electrostatic adsorption clutch of the master manipulator; Force feedback is achieved by pressurizing the electrostatic adsorption clutch through the control system.

[0014] The motion mapping of the master hand is completed on the slave manipulator through the master-slave isomorphic joint mapping algorithm, the Euler angle of each sensor is obtained by converting the quaternion to the Euler angle, and the Euler angles of the sensors at both ends of the finger joint are subtracted to obtain the joint angle.

[0015] The working process of pressurizing the electrostatic adsorption clutch to realize force feedback through the control system is as follows: Select the voltage generated by DA and micro high-voltage power supply control. When the voltage is zero, the electrostatic adsorption clutch does not work, and the motion electrode fixed on the fingertip can move freely with the human hand. When the slave manipulator generates force feedback, the control system calculates the required voltage according to the force-voltage theoretical model, drives the electrostatic adsorption clutch to adsorb, and hinders the movement of the human hand when the human hand moves. The actual force generated is fed back through the force sensor connected to the motion electrode and compared with the theoretical force; Based on the compared force error, it is fed back to the force-voltage theoretical model for recalculation, forming a feedback loop to generate more accurate braking force and realize force feedback.

[0016] Compared with the prior art, the present invention has the following beneficial effects: The invention provides an electrostatic adsorption clutch force feedback data glove based on a teleoperation system and a design method thereof, comprising a hand posture capture part and a kinesthetic force feedback part, wherein the hand posture capture part comprises: a glove main body part, a crystal gyroscope is arranged on the fingertips, a sensor stacking structure is arranged on the fingers, an FPC soft board is fixed on the fingers through a Velcro strap, a nine-axis IMU sensor is welded on the FPC soft board, a first integrated PCB board is fixed on the back of the hand, and the first integrated PCB board comprises a posture capture module, a system on a chip and a Bluetooth communication module; the kinesthetic force feedback part comprises an electrostatic adsorption clutch, a back of the hand guide rail is fixed on the back of the hand, a fixed electrode and a moving electrode are arranged on the back of the hand guide rail, the tail end of the moving electrode is fixed on the back of the hand guide rail through an elastic rope, the front end of the moving electrode is connected to a tension sensor, and is fixedly connected to a fingertip cover through a steel wire rope passing through a sleeve guide rail, and a second integrated PCB board is fixed on the forearm wearing the glove. This data glove integrates a nine-axis IMU sensor, a crystal gyroscope, and a posture capture module to achieve high-precision real-time capture of hand postures, and can accurately reflect the bending angle and yaw angle of the fingers; the on-chip system uses the fully programmable on-chip system ZYNQ, and uses ZYNQ's parallel processing capabilities to greatly improve the efficiency of data acquisition and calibration, which not only improves the upload frame rate of the hand posture data packet, but also greatly reduces the sensor calibration time; the electrostatic adsorption clutch system is used to precisely control the voltage value between the electrodes to achieve the obstruction of finger movement, thereby providing a real and delicate force feedback experience. Through accurate posture capture and force feedback, the operator's operating accuracy and efficiency can be improved, and the difficulty of operation and the risk of misoperation can be reduced.

[0017] Furthermore, the hand gesture capture part uses the programmable logic PL end, and the kinesthetic force feedback part uses the processing system PS end. The PL can connect and communicate with various sensors, actuators and other external devices to achieve information sharing and exchange, and the PL system is easy to expand and upgrade to adapt to possible future function additions or changes. The processing system PS end greatly improves the processing efficiency and accuracy of kinesthetic force feedback.

[0018] Furthermore, a solution algorithm and a fingertip mapping algorithm that avoid singularity solution failure are adopted to ensure the accuracy and stability of the motion mapping from the master hand to the slave hand, and effectively avoid singularities during the motion process.

[0019] Furthermore, a complete electrostatic adsorption braking force feedback system was established. Through voltage application, force signal collection, comparison and proportional feedback, precise driving of the electrostatic adsorption clutch was achieved, thereby achieving precise control of the force feedback.

[0020] Furthermore, the design of the data gloves takes into account the convenience and comfort of wearing. The sensors and electrodes are stably fixed through structures such as Velcro straps and fixing straps. It is equipped with a sensor synchronization calibration system, including a synchronization calibration mechanical board and a synchronization calibration software system, which facilitates the precise calibration of each sensor and improves the accuracy and reliability of the system.

[0021] Furthermore, the data glove and the design method thereof are applicable to various remote operation systems, such as telemedicine, remote control, virtual reality and other fields, providing the operator with a more realistic and intuitive operation experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is the hardware structure diagram of the posture capture module of the force feedback data glove; Figure 2 This is a block diagram of the control system composition of the posture capture module of the force feedback data glove; Figure 3 This is the hardware structure diagram of the force feedback module of the force feedback data glove; Figure 4 It is a block diagram of the control system composition of the force feedback module of the force feedback data glove; Figure 5 The hardware structure diagram for synchronization calibration; Figure 6 It is the flow chart of PVTC film preparation; Figure 7 This is the diagram of the homemade H-bridge module; Figure 8 This is the RTL level circuit diagram of the lower computer of the posture capture module of the force feedback data glove; Fig. 9 This is a framework diagram of the data synchronization acquisition method for the posture capture module of the force feedback data glove; Fig.10 This is a system module framework diagram of the posture capture module of the force feedback data glove; Fig.11 This is the state machine transition diagram of the posture capture module of the force feedback data glove; Fig.12 It is a visual interface for force feedback data gloves; Fig.13 This is the posture solution flow chart of the force feedback data gloves; Fig.14 Software design flow chart for the force feedback module of the force feedback data glove; Fig.15 This is the overall working flow chart of the system involved in the present invention; Fig.16 This is a schematic diagram of the physiological structure of the human hand; Fig.17Schematic diagram of the automatic control process of the electrostatic adsorption clutch.

[0023] Explanation of the reference numerals in the figure: 1. crystal gyroscope; 2. FPC soft board; 3. nine-axis IMU sensor; 4. system on chip; 5. first integrated PCB board; 6. Bluetooth communication module; 7. posture capture module; 8. back of hand guide; 9. fixed electrode; 10. moving electrode; 11. tension sensor; 12. sleeve guide; 13. fingertip cover; 14. elastic rope; 15. second integrated PCB board. DETAILED DESCRIPTION

[0024] In order to further understand the content of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the embodiments are only for explaining the present invention and are not intended to limit it.

[0025] Embodiment 1: The electrostatic adsorption clutch force feedback data glove based on the teleoperation system includes a hand posture part and a kinesthetic feedback part, wherein: like Figure 1 As shown, the hand gesture capture part includes: a glove main body, a crystal gyroscope 1 is arranged on the fingertips, the crystal gyroscope 1 has high precision, is not affected by magnetic field and has a high upload frame rate, a sensor stacking structure is arranged on the finger, an FPC soft board 2 is fixed on the finger by a Velcro strap, an inertial sensor is welded on the FPC soft board 2, a first integrated PCB board 5 is fixed on the back of the hand, and a gesture capture module 7, a system on chip 4 and a Bluetooth communication module 6 are welded on the first integrated PCB board 5; the gesture capture module 7 is used to collect hand movements in real time, the system on chip 4 is used to preprocess, filter and encode the collected hand data, and the Bluetooth communication module 6 is used to transmit the processed hand data to the host computer.

[0026] like Figure 3 As shown, the kinesthetic force feedback part includes: an electrostatic adsorption clutch; a hand back guide rail 8 is fixed on the hand back, and a fixed electrode 9 and a motion electrode 10 that moves with the fingers are arranged on the hand back guide rail 8. The tail end of the motion electrode 10 is fixed to the hand back guide rail 8 through an elastic rope 14, and the front end of the motion electrode 10 is connected to a tension sensor 11, and is fixedly connected to the fingertip sleeve 13 through a steel wire rope passing through the finger sleeve guide rail 12. A second integrated PCB board 15 is fixed on the forearm of the wearer of the force feedback data glove, and the second integrated PCB board 15 includes a microprocessor, a DA module, a micro high-voltage power supply and a high-voltage H-bridge module.

[0027] Preferably, the electrostatic adsorption clutch is selected to select a PVTC (P (VDF-TrFE-CFE)) material with a higher dielectric constant as the dielectric layer, taking into account the maximum braking force of a human hand and the back area of ​​the hand.

[0028] Embodiment 2: The operation method of the electrostatic adsorption clutch force feedback data glove based on the remote control system is as follows: S1: Fix the back-of-hand guide rail 8 on the back of the hand; stick the fixed electrode 9 on the back-of-hand guide rail 8; install the fingertip cover 13 on the fingertips, connect the fingertip cover 13, the sleeve guide rail 12, the tension sensor 11 and the moving electrode 10 to form a transmission mechanism; the transmission mechanism passes through the back-of-hand guide rail 8 and is fixed on the guide rail through the elastic rope 14; fix the second integrated PCB board 15 on the forearm, and connect it to the fixed electrode 9 and the moving electrode 10 through two wires to drive the data glove to follow the movement of the human hand; fix the FPC soft board 2 on the finger through a Velcro tie; fix the first integrated PCB board 5 on the back of the glove, and connect the various parts through wires.

[0029] S2: The posture capture module 7 captures all joint postures of the human hand in real time, captures the bending angle of the joints through the inertial sensors fixed at both ends of each finger joint, and captures the yaw angle of each finger MCP joint through the crystal gyroscope 1 fixed on the fingertip; then the master-slave isomorphic joint mapping algorithm is used to convert the angle information of each joint of the slave manipulator, and the motion mapping from the master hand to the slave hand is realized through the master-slave communication system.

[0030] S3: The feedback force of the slave-end manipulator is obtained through the slave-end force sensor, transmitted to the master-end force feedback glove through master-slave communication, and converted into the master hand feedback force through the master-slave force mapping algorithm; the feedback force is converted into a voltage value of the two input electrodes through the electrostatic adsorption clutch system, and the accurate voltage value is obtained through the master-end force feedback system, and kinesthetic force feedback is achieved by hindering finger movement.

[0031] Preferably, the inertial sensor in S2 is a nine-axis IMU3 sensor 3 with high precision and high upload frame rate. The angle sensor is attached to the finger, and the accelerometer, gyroscope, and magnetometer are combined to perform posture fusion to calculate the posture of the object to which the sensor is attached, and then the movement angle of the joint is calculated through the finger joint posture, thereby realizing the motion measurement of each finger joint angle.

[0032] Preferably, the gyroscope in S2 is a crystal gyroscope 1 with high precision, no interference from magnetic field and high upload frame rate, and the motion measurement of the yaw angle of each finger is achieved by outputting the yaw angle attitude.

[0033] Preferably, the system on chip 4 in S1 selects a field programmable gate array FPGA, which has highly flexible hardware programmability, can dynamically adjust circuit logic according to demand, supports parallel processing and efficient computing, and is particularly suitable for data-intensive and real-time tasks. It has significant advantages in low latency, high throughput, power consumption optimization, etc.

[0034] Preferably, a solution algorithm that avoids singularity solution failure and a more accurate fingertip mapping algorithm are applied in S2 to complete the motion mapping from the master hand to the slave hand, a threshold is set at the singularity, and the specific joint angle of the slave end is obtained by direct mapping of the master end joint to the slave end joint to achieve motion mapping.

[0035] Preferably, a complete electrostatic adsorption braking force feedback system is established in S3, and a more accurate voltage is obtained by applying voltage, collecting, comparing and proportionally feedback force signals, so as to complete the electrostatic adsorption clutch drive and realize force feedback.

[0036] Embodiment 3: This embodiment relates to a design method of an electrostatic adsorption clutch force feedback data glove based on a teleoperation system. The entire teleoperation system includes a master end system, a master-slave communication system and a slave end system.

[0037] The master system includes the designed force feedback data glove and the master control system. The force feedback data glove measures the data of each joint angle of the human hand in real time, samples and processes the signals of each sensor through the data synchronization acquisition system, and then obtains the posture and movement information of the user's hand by solving the posture data through the computer. The master control system drives the master force feedback data glove to work and transmits the force feedback information to the operator. The generation of teleoperation system commands, data transmission, data processing, and force feedback data glove control are all completed on the master control system.

[0038] The Internet acts as a communication link to connect the master and slave ends.

[0039] The slave system receives the teleoperation system commands transmitted from the master system, and feeds back some key systems in the slave system to the master system, and then feeds back to the operator, so that the operator can adjust the teleoperation system commands according to the actual situation. That is, the slave manipulator receives the human hand motion information (including joint angle, motion speed, etc.) detected by the data gloves at the master end and converts it into its own motion information to achieve real-time motion mapping. At the same time, when interacting with the slave environment, the sensors (force sensors, etc.) located on the slave manipulator perceive the environmental information, and finally transmit the perceived environmental information back to the master server through the slave server via the Internet, and transmit the feedback information to the human hand through the gloves.

[0040] 1. Hardware Design Figure 1 and Figure 2 The posture capture module of the force feedback data glove mainly includes a suede glove, 18 nine-axis IMU sensors 3, 5 crystal gyroscopes 1 angle sensor, a XC7z020CLG400-2 model chip system of the ZYNQ-7000 series, a Bluetooth communication module 6 and a battery module.

[0041] Figure 3 and Figure 4 The invention is a data glove force feedback device, which mainly comprises an electrostatic adsorption clutch, a transmission mechanism, a fingertip cover 13 and a control system thereof.

[0042] The present invention uses ZYNQ as the main control chip, and the XC7z020CLG400-2 controller is installed on the first integrated PCB board 5 on the back of the hand, which is the core of the entire hand motion capture module. ZYNQ is a fully programmable system-on-chip launched by Xilinx. It perfectly integrates the software programmability of the processor with the hardware programmability of the FPGA to provide unparalleled system performance, flexibility and scalability. ZYNQ consists of two main parts: a processing system (PS) composed of a dual-core ARM Cortex-A9 as the core, and a programmable logic (PL) part equivalent to a piece of FPGA.

[0043] like Figure 2 As shown, the hand gesture capture part of the present invention uses the system PL end to communicate data with each sensor through the UART communication interface and the FPC soft board 2, synchronously collects the data of each sensor, and transmits it to the Bluetooth communication module 6 through the UART interface after data processing. The Bluetooth communication module 6 receives the data packet through the UART interface and transparently transmits it to the host computer Bluetooth module. The host computer Bluetooth module is connected to the host computer USB interface through the UART interface to USB module.

[0044] The present invention adopts a high-performance angle sensor module (ATK-MS901M) and a single-axis crystal gyroscope module (HWT101) as a capture and measurement unit for the human hand posture. The ATK-MS901M module is a ten-axis high-performance angle sensor module launched by Zhengdian Atom. The module integrates multiple high-precision sensors: gyroscope, accelerometer, magnetometer, barometer, and uses a 32-bit 72MHz high-performance microprocessor to quickly solve the current real-time motion posture of the module. The ATK-MS901M module communicates with the external main control chip through the UART interface and directly outputs the posture data through the UART interface. Therefore, the external main control does not need to perform complex posture calculations, reducing the load of motion processing operations on the application end. The HWT101 module is a single-axis high-performance three-dimensional motion posture measurement unit launched by Witt Intelligence. The module integrates a high-precision crystal gyroscope 1, uses a high-performance microprocessor and advanced dynamics solution and Kalman dynamic filtering algorithm, and can quickly solve the current real-time motion posture of the module. The HWT101 module communicates with the external main control chip through the UART interface and directly outputs the heading attitude angle. The external main control does not need to perform complex attitude calculations, which reduces the load of motion processing operations on the application end.

[0045] The present invention uses a self-drawn FPC soft board 2 to connect each sensor. The FPC soft board 2 is a flexible circuit board made of flexible materials (such as polyimide or polyester film) and has the characteristics of being bendable, thin, and durable. Unlike traditional rigid PCB boards, it can provide reliable electrical connections in narrow or foldable spaces, and has significant space and weight advantages in complex circuit designs. The present invention welds each inertial sensor on the FPC soft board 2 through a gold-plated stamp to form a finger module, which is connected to the main control module through a silicone DuPont line.

[0046] The present invention adopts Bluetooth communication module 6 to upload data packets of the host computer. MX-06A of Mixiang Technology is selected. The module integrates CYPRESS Bluetooth 4.2 LE+BR / EDR dual-mode chip with ARM Cortex-M3 as the core, integrated Bluetooth protocol baseband, MCU, and high-gain radio frequency PCB antenna.

[0047] like Figure 4 As shown, the force feedback glove of the present invention uses the PS end to receive the force feedback signal from the slave end through the UART interface. The force feedback signal is decoded, amplified and converted by the ZYNQ chip at the PS end, and the force feedback signal is converted into an analog signal through the DA module. The micro high-voltage power supply receives the analog signal and generates a corresponding voltage output according to the size and type of the signal. These voltage outputs are used to drive the high-voltage H bridge, and the high-voltage H bridge drives the electrostatic adsorption clutch to generate the corresponding passive kinesthetic force, and then forms a feedback loop through the force sensor at the master end, so as to obtain a more accurate feedback force.

[0048] Further, such as Figure 5 As shown in the figure, a sensor synchronous calibration system is designed, including a synchronous calibration mechanical board and a synchronous calibration software system. The calibration board is designed with a plastic bolt tightening device on the top of each finger sensor and a positioning groove on the bottom to ensure that the sensor remains fixed during the calibration process and does not shake at will. The principle of synchronous calibration is similar to the principle of synchronous collection. In contrast to synchronous collection, the registers of each sensor are operated to perform different types of calibration.

[0049] like Figure 6As shown, the present invention adopts an electrostatic adsorption clutch based on PVTC, the area of ​​PVTC is 14mm*55mm, and the PVTC film is prepared by a solution volatilization method. P(VDF-TrFE-CFE) powder with a monomer ratio of 40: 30: 30 is selected as the solute, DMAC (N, N-dimethylacetamide) is selected as the solvent, and a certain mass is weighed by an electronic balance according to the standard of 14wt% mass fraction of the solute to prepare a solution; then the above solution is placed in a magnetic stirrer, stirred at 80°C at a speed of 300r / min for 12h, and then stirred at room temperature for 24h until the solute is uniformly dispersed in the solvent; then the solution is poured into a designed groove plate with grooves, scraped and ground, and placed on an adjustable water platform placed in a vacuum drying oven and leveled by a leveler to ensure the solution is leveled, dried and defoamed at 60°C for 5h, and then annealed at 120°C for 2h, cooled to room temperature, and the film is removed from the plate to obtain a PVTC film. The electrostatic adsorption clutch is then obtained by covering the electrodes with a dielectric layer, and the electrostatic adsorption clutch and tension sensor are encapsulated by square 3D printed parts with a size of 20mm*70mm*30mm.

[0050] The present invention uses a DA module to convert discrete digital signals into continuous analog signals to obtain the analog voltage required by the micro high-voltage power supply. The DA module is a dual-channel high-speed digital-to-analog conversion module (ATK_DUAL_HS_DA) of Zhengdian Atom, with a digital-to-analog conversion bit number of 10 bits and a maximum conversion speed of 125MSPS, that is, it is connected to the 10-bit parallel port of ZYNQ, and a digital signal of 000~1ff is input to output an analog voltage of +5V~-5V.

[0051] The present invention uses a micro high-voltage power supply to generate high voltage electricity. The KDHM-C series micro high-voltage power supply module is a special DC-DC power supply module with low voltage input and high voltage output. It is small in size and has a fast output short-circuit protection function, allowing the output to be directly short-circuited without damaging the module. The output current is only 0~0.5mA, which is relatively safe for the human body and suitable for wearable devices. The output voltage can be proportionally adjusted to 0-1kv by inputting 0~2.5V, and the accuracy mainly depends on the input voltage accuracy.

[0052] like Figure 7 As shown, the present invention adopts a self-made high-voltage H-bridge module. The electrostatic adsorption clutch is equivalent to a capacitor. If the same polarity voltage is input for a long time, the power will be lost slowly and the space charge will be easily accumulated, which will slow down the speed of the clutch disconnection. The AC voltage can accelerate the start speed of the electrostatic adsorption clutch and eliminate the charge accumulation.

[0053] The present invention adopts ZNLBM-VD type tension and pressure dual-purpose sensor, which is a special sensor specially developed by our factory for the medical industry. It uses foil strain gauges attached to alloy steel elastic bodies, and has the characteristics of good sealing and long-term operation stability. Its range is 10KG, and the widest size is Ø13mm*8mm.

[0054] The present invention adopts a power module to provide direct current to the control system, and adopts a lithium battery with an output voltage of 5V, a capacity of 6600mAh, and a size of 55mm*70mm*19mm.

[0055] 2. Software Design The lower computer of the data glove gesture capture module is developed using Xilinx's Vivado software to build a Figure 8 The overall framework of the multi-sensor data synchronization acquisition method based on FPGA is shown in the RTL level circuit diagram. Fig. 9 As shown in the figure, for the main control module, there are two transceiver loops. One is the collection and upload of attitude data, including data reception, synchronization, analysis, packaging, and transmission; the other is the reception and release of calibration and initial commands, which is consistent with the content of the above loop.

[0056] The data synchronization acquisition system of the multi-sensor system is divided into three layers: top-level module, middle-level module and bottom-level module. The module framework of the system is as follows: Fig.10 As shown in the figure, the top-level module exposes the physical interface for external connection, and instantiates the middle-level modules such as five fingers and back of hand and some bottom-level modules; the middle-level module is mainly established for the reuse of modules, and there are 6 modules, including five fingers and back of hand, which are responsible for the data packaging and completion mark of the module; the functions of the bottom-level modules are more functional, among which the Decode module is only responsible for the analysis of sensor data, and uses the Gray code three-stage state machine to parse the data, such as Fig.11 As shown in the figure, this involves cross-clock data transmission, where data is transmitted from the slow clock of the sensor to the fast clock of the main control module. The fast clock frequency is twice that of the slow clock, so it only needs two beats to be stored.

[0057] The host computer uses Unity to perform data fusion processing and action visualization, such as Fig.12 The algorithm flow chart is shown as Fig.13 As shown. After establishing a connection with the serial port, data is received and two threads are started for data analysis and initialization. Before the data is analyzed to be sufficient for initialization, the posture visualization is not performed. When the data is sufficient, the initialization is started. During this period, the hand remains still and waits for the initialization to complete. After the initialization is successful, the initial posture of each sensor is obtained, the serial port cache is cleared, and the thread is terminated. After that, the data is analyzed and the posture is solved, and the visualization is performed in real time.

[0058] Use the PS end of ZYNQ to design the software of the main end force feedback system, such as Fig.14 First, each peripheral is initialized, and then the slave force signal transmitted through the UART interface is analyzed, and it is converted into a digital signal of the required voltage through the theoretical relationship for output, and then the force feedback signal from the master end is received through the UART interface and compared with the actual force. If the comparison value is not within the threshold, the next voltage conversion is performed until it meets the requirements within a certain threshold.

[0059] 3. System operation process like Fig.15 As shown, the gesture capture module 7 of the data glove first collects the motion of the human hand, and then completes the motion mapping of the master hand on the slave manipulator through the master-slave isomorphic joint mapping algorithm. Then the slave manipulator contacts the environment to generate contact force, and the force sensing device at the slave end feeds back the force signal, which is transmitted to the electrostatic adsorption clutch of the master hand, and the control system pressurizes the electrostatic adsorption clutch to achieve corresponding force feedback.

[0060] The specific steps include: The gesture capture module of the data glove is used to collect hand motion information. Fig.16 As shown, first analyze the physiological structure of the human hand and clearly understand the movement rules of the human hand. The human hand can be divided into three parts according to the bones: wrist, fingers and palm. Here we only focus on the movement of the fingers. There are 14 phalanges in the hand. The fingers can be divided into thumb and four fingers according to their similarities. The four fingers include index finger, middle finger, ring finger and little finger. The PIP and DIP joints of the four fingers and the IP and MCP joints of the thumb are hinge-type joints with flexion / extension movement ability and only one degree of rotation. The MCP joints of the four fingers are ankle-type joints with two degrees of freedom of flexion / extension and abduction / adduction. The CM joint of the thumb is a saddle-type joint with two degrees of freedom of flexion / extension and abduction / adduction.

[0061] The collected master hand motion information is converted into the joint angles of the slave manipulator through the master-slave isomorphic joint mapping algorithm to achieve motion mapping from the master hand to the slave hand. The collected data packets are solved by converting quaternions to Euler angles:

[0062] Since the values ​​of arctan and arcsin are in the range arrive There is only 180° between them, while the range of rotation around a certain axis is 360°, so the atan2 function is used instead of the arctan function:

[0063] In particular, when the pitch angle (Pitch) When , a singularity occurs, and the degree of freedom is lost, that is, the yaw angle (Yaw) and the roll angle (Roll) become one degree of freedom. At this time, using the above formula to calculate the Euler angle based on the quaternion will cause problems: The domain of is [−1,1], so ,when When (in the program, floating point numbers cannot be directly judged as equal, so a reasonable threshold should be used), the pitch angle , put it into the forward formula to calculate the quaternion (w, x, y, z), and then the parameters in the atan2 function in the formula are all 0, that is, there is a 0 / 0 situation, which cannot be calculated. So in the program, Two trace thresholds are set nearby. When within these thresholds, special cases are handled specially. When it is around 0.5, the calculation formula is as follows:

[0064] When it is around -0.5, the calculation formula is as follows:

[0065] In this way, the Euler angles of each sensor are obtained, and the joint angles can be obtained by subtracting the Euler angles of the sensors at both ends of the finger joint. The master-slave isomorphic joint mapping algorithm is used, that is, the joints are mapped one by one, so the obtained joint angles can be directly mapped to the slave end.

[0066] The perception ability of the main operator is realized by the force feedback glove, which feeds back the force generated by the slave manipulator to the operator's hand, forming a control system of the force glove.

[0067] like Fig.17 As shown in the figure, the automatic control process of the electrostatic adsorption clutch is: select the voltage generated by DA and the micro high-voltage power supply control. When the voltage is zero, the electrostatic adsorption clutch does not work, and the motion electrode fixed on the fingertip can move freely with the human hand. When force feedback is generated from the end, the control system calculates the required voltage according to the force-voltage theoretical model to drive the electrostatic adsorption clutch to adsorb. When the human hand moves, it hinders the movement of the human hand. The actual force generated is fed back by the force sensor connected to the motion electrode, compared with the theoretical force, and the force error is fed back to the force-voltage theoretical model for recalculation, forming a feedback loop to generate more accurate braking force and realize force feedback.

[0068] The calculation process of the force-voltage theory model is: The magnitude of the feedback force output by the electrostatic adsorption clutch is determined by the voltage, dielectric constant of the dielectric layer, contact area of ​​the two electrode plates, distance between the two electrode plates, etc. After the dielectric film is determined, the magnitude of the output force of the force feedback data glove is directly determined by the input voltage. The theoretical output force calculation formula of the electrostatic adsorption clutch is:

[0069] in, Indicates the dielectric constant of the insulating layer (F / m), represents the vacuum dielectric constant (F / m), represents the overlapped area of ​​the two electrodes (m 2 ), represents the voltage between the two electrodes (V), represents the distance between the electrodes on both sides (m); Braking force The calculation formula is as follows:

[0070] Represents the friction coefficient between the two electrodes.

[0071] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An electrostatic adsorption clutch force feedback data glove based on a teleoperation system, characterized in that: Including hand posture capture part and kinesthetic force feedback part; The hand gesture capture part comprises: a glove main body, a crystal gyroscope (1) is arranged at the fingertips, a sensor stacking structure is arranged on the fingers, an FPC soft board (2) is fixed to the fingers by means of a Velcro strap, an inertial sensor is welded on the FPC soft board (2), a first integrated PCB board (5) is fixed on the back of the hand, and the first integrated PCB board (5) comprises a gesture capture module (7); The kinesthetic force feedback part comprises: an electrostatic adsorption clutch, a back of hand guide rail (8) fixed on the back of the hand, a fixed electrode (9) and a moving electrode (10) arranged on the back of the hand guide rail (8), the rear end of the moving electrode (10) being fixed to the back of the hand guide rail (8) via an elastic rope (14), the front end of the moving electrode (10) being connected to a tension sensor (11), and being fixedly connected to a fingertip cover (13) via a steel wire rope passing through a sleeve guide rail (12), and a second integrated PCB board (15) being fixed on the forearm wearing the glove; The integrated PCB board is a fully programmable system on chip ZYNQ, and the inertial sensor is a nine-axis IMU sensor (3).

2. The electrostatic adsorption clutch force feedback data glove based on the teleoperation system according to claim 1 is characterized in that: The fully programmable system-on-chip ZYNQ consists of two parts, including a processing system PS and a programmable logic PL. The hand gesture capture part uses the programmable logic PL end, and the kinesthetic force feedback part uses the processing system PS end.

3. The electrostatic adsorption clutch force feedback data glove based on the teleoperation system according to claim 1, characterized in that: The sensor stack structure includes an angle sensor, an accelerometer, a gyroscope and a magnetometer. The posture fusion solution is performed through the data of the sensor stack structure to obtain the posture of the object to which the angle sensor is attached, and the movement angle of the joint is calculated in combination with the finger joint posture.

4. The electrostatic adsorption clutch force feedback data glove based on the teleoperation system according to claim 1, characterized in that: Here’s how to use it: Assembling the data glove: fixing the hand back guide rail (8) on the hand back, pasting the fixed electrode (9) on the hand back guide rail (8), installing the fingertip cover (13) on the fingertip, connecting the fingertip cover (13), the sleeve guide rail (12), the tension sensor (11) and the moving electrode (10) to form a transmission mechanism, fixing the second integrated PCB board (15) on the forearm, connecting the fixed electrode (9) and the moving electrode (10) respectively through wires to drive the data glove to follow the movement of the human hand; fixing the FPC soft board (2) on the finger through a Velcro strap, fixing the first integrated PCB board (5) on the back of the glove, and connecting the various parts through wires; The posture capture module (7) is used to capture the postures of all joints of the human hand in real time. The inertial sensors fixed at both ends of each finger joint are used to capture the bending angle of the joint. The crystal gyroscope (1) fixed at the fingertip is used to capture the yaw angle of each finger MCP joint. The master-slave isomorphic joint mapping algorithm is then used to convert the angle information of each joint of the slave manipulator, and the motion mapping from the master hand to the slave hand is realized through the communication link. The feedback force of the slave manipulator is obtained and transmitted to the force feedback glove of the master through master-slave communication. The master hand feedback force is converted through the master-slave force mapping algorithm. The feedback force is converted into a voltage value input to two electrodes through an electrostatic adsorption clutch system, and an accurate voltage value is obtained through a main-end force feedback system, thereby achieving kinesthetic force feedback by hindering finger movement.

5. The electrostatic adsorption clutch force feedback data glove based on the teleoperation system according to claim 4 is characterized in that: The master-slave isomorphic joint mapping algorithm uses a solution algorithm that avoids singularity solution failure and a fingertip mapping algorithm with higher accuracy to complete the motion mapping from the master hand to the slave hand.

6. The design method of the electrostatic adsorption clutch force feedback data glove based on the teleoperation system according to claims 1 to 5, characterized in that: It includes a master-end system, a master-slave communication system and a slave-end system, wherein the master-end system includes a force feedback data glove and a master-end control system, which are used to measure the data of each joint angle of the human hand in real time, sample and process the signals of each sensor, and obtain the posture and movement information of the user's hand by solving the posture data by computer; the slave-end system receives the remote operation system command transmitted by the master-end system, and feeds back the information in the slave-end system to the master-end system; the master-slave communication system is used to realize the communication between the master-end system and the slave-end system.

7. The design method of the electrostatic adsorption clutch force feedback data glove based on the teleoperation system according to claim 6 is characterized in that: It includes a synchronous calibration mechanical board and a synchronous calibration software system, which are used to calibrate each sensor.

8. The design method of the force feedback data gloves based on the force feedback teleoperation system according to claim 6, characterized in that: The operation process is as follows: Collect the movement of human hands; The motion mapping of the master hand is completed on the slave manipulator through the master-slave isomorphic joint mapping algorithm; The slave end manipulator contacts the environment to generate contact force; The slave manipulator senses the feedback force signal of the environmental contact force and transmits the feedback force signal to the electrostatic adsorption clutch of the master manipulator; Force feedback is achieved by pressurizing the electrostatic adsorption clutch through the control system.

9. The design method of the force feedback data gloves based on the force feedback teleoperation system according to claim 8, characterized in that: The motion mapping of the master hand is completed on the slave manipulator through the master-slave isomorphic joint mapping algorithm, the Euler angle of each sensor is obtained by converting the quaternion to the Euler angle, and the Euler angles of the sensors at both ends of the finger joint are subtracted to obtain the joint angle.

10. The design method of the force feedback data gloves based on the force feedback teleoperation system according to claim 8, characterized in that: The working process of pressurizing the electrostatic adsorption clutch to realize force feedback through the control system is as follows: Select the voltage generated by DA and micro high-voltage power supply control. When the voltage is zero, the electrostatic adsorption clutch does not work, and the motion electrode fixed on the fingertip can move freely with the human hand. When the slave manipulator generates force feedback, the control system calculates the required voltage according to the force-voltage theoretical model, drives the electrostatic adsorption clutch to adsorb, and hinders the movement of the human hand when the human hand moves. The actual force generated is fed back through the force sensor connected to the motion electrode and compared with the theoretical force; Based on the compared force error, it is fed back to the force-voltage theoretical model for recalculation, forming a feedback loop to generate more accurate braking force and realize force feedback.

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