187 results about "Exoskeleton robot" patented technology

The invention relates to the technical field of robot control and somatosensory interaction, and particularly discloses a knee joint exoskeleton robot control system based on somatosensory interaction. The system comprises a somatosensory signal acquisition and fusion module, a personalized dynamic model construction module, an adaptive intention decision module, a variable impedance compliance control module and a rehabilitation process evaluation and parameter self-tuning module. Through cooperative work of the modules, precise recognition of the motion intention of a wearer, online construction of an individualized biomechanical model and flexible and adaptive motion control are achieved, control parameters can be automatically adjusted according to the rehabilitation process, and therefore the flexibility and individuation level of man-machine interaction and the effectiveness of rehabilitation training are improved.

The invention discloses a pathology adaptive prediction control method for a lower limb rehabilitation exoskeleton robot, and belongs to the technical field of rehabilitation robot control. The method comprises the steps that the joint angle, the angular speed and the man-machine interaction torque of the lower limb rehabilitation exoskeleton robot are collected in real time, and a kinetic equation of the lower limb rehabilitation exoskeleton robot is constructed; on the basis of the kinetic equation of the lower limb rehabilitation exoskeleton robot, parameter vectors representing the current pathological features of the patient are estimated online, so that a prediction model in the lower limb rehabilitation exoskeleton robot is updated, and the optimal auxiliary torque is solved. The intelligent brain of the exoskeleton robot can be deeply fused with the real-time state of the body of the patient, and rehabilitation training which is really personalized and self-adaptive and can effectively promote neural function recovery is provided for the patient.

The invention discloses a lower limb exoskeleton robot layered cooperative walking aid control method. The method comprises the steps of data acquisition and preprocessing; human-machine coupling dynamics modeling is carried out, and required moments tau < hip >, tau < knee > and tau < ankle > of the hip joint, the knee joint and the ankle joint are obtained; low-layer joint control, including hip joint moment, knee / ankle virtual impedance moment and friction compensation calculation; middle-layer multi-axis cooperation and gait phase judgment; high-rise energy is optimally distributed, assistance is distributed to three joints in a phase and a safety boundary, meanwhile, the requirements for labor saving and stability are considered, a minimization problem is written in a unified mode, J serves as the total amount, and torque of the hip joint, torque of the knee joint and torque of the ankle joint are solved in a combined mode; according to the step-by-step self-adaption of myoelectricity driving, in order to cope with human body fatigue changes, step-by-step updating is carried out on the virtual stiffness within the movement distance. The method has the advantages of improving man-machine cooperation level, man-machine adaptability and walking aid efficiency.

The invention relates to an exoskeleton robot control method and device and an exoskeleton robot. The method comprises the following steps: determining an activity parameter according to a signal collected by a sensor; identifying a plurality of motion intentions according to the activity parameters, judging motion identifiers under the motion intentions, and determining a plurality of motion identifiers; performing state transition according to the plurality of action identifiers by utilizing a finite-state machine to obtain a target sub-state; a plurality of motion modes are preset in the finite-state machine, and each motion mode corresponds to at least one sub-state; and controlling the power unit according to the control instruction corresponding to the target sub-state. According to the method, the motion intention recognition and the finite-state machine are combined to complete the operation state transition, so that the misjudgment rate of state recognition can be reduced, and the robustness of the finite-state machine is improved; the multiple preset motion modes of the finite-state machine are divided into the sub-states, the situation of wrong assistance can be eliminated to a certain degree, misoperation of the exoskeleton robot is avoided, and the assistance control accuracy is improved.

The invention discloses an exoskeleton robot abnormal working condition automatic response and risk avoiding decision-making method, and relates to the technical field of exoskeleton, and the method comprises the steps: deploying a plurality of types of sensors to synchronously collect environment data, human physiological data and exoskeleton operation data, and carrying out the preprocessing to remove interference; through fusion of abnormal harmonic detection and a finite-state machine, dangerous working conditions such as wind speed abrupt change are identified, and grades are judged; monitoring eye movement and heart rate variability data in real time, quantifying cognitive load and grading; a decision rule base is constructed, and joint locking and other adaptive risk avoiding decisions are generated in combination with working condition types, grades and cognitive loads; the controller drives the execution mechanism to execute a decision, continuously monitors data at a frequency, dynamically adjusts the decision or recovers a normal mode. According to the method, dangerous working conditions are accurately identified through multi-source data fusion, adaptive risk avoiding measures are automatically triggered, a power assisting strategy is dynamically adjusted in combination with cognitive loads, and operation flexibility and physical output are balanced.

A mobility assistance exoskeleton robot, comprising: a waist support structure module (1), a waist rod module (2), a joint drive module (3), a leg rod module (4), and a binding system (5). The waist rod module (2) comprises waist rod module assemblies; two waist rod module assemblies are provided, said two assemblies being symmetrically arranged relative to the waist support structure module (1).

The utility model relates to the technical field of exoskeleton robots, in particular to a binding mechanism of a walking aid robot, which comprises a shoulder and back binding belt, a waist binding belt and a leg binding belt, the shoulder and back binding belt is provided with a plurality of shoulder and back connecting ends used for being connected with a main body frame; connecting belts are arranged on the shoulder and back connecting ends in a one-to-one correspondence mode and detachably connected with the shoulder and back connecting ends, buckles are arranged on the connecting belts, and buckling bases used for being matched with the buckles are arranged on the main body frame; and the waist bridle and the leg bridles are detachably connected to the main body frame. The fixing structure has the effect of solving the problem that the fixed connection between the bridle and the main body frame or the joint part is inconvenient to disassemble and replace.

The application relates to the technical field of medical rehabilitation robots, in particular to a safe upper limb rehabilitation exoskeleton robot, which comprises a fixing frame and a mechanical arm arranged on the fixing frame and used for assisting the movement of a patient's arm, the mechanical arm comprises, in sequence, a shoulder joint vertical folding and unfolding module, a shoulder joint horizontal folding and unfolding module, a shoulder joint flexion and extension module, an elbow joint flexion and extension module, a wrist joint flexion and extension module and a lower arm rotating module, the mechanical arm can be suitable for a left arm or a right arm by switching left and right states. Each module of the mechanical arm is provided with a mechanical limiting structure used for limiting the activity range of the corresponding module, and the mechanical limiting structure can switch left and right states, and is used for synchronously switching when the mechanical arm switches left and right states to ensure the safety of the patient. The spring positioning pin is used for adjustably limiting, the application can realize the left and right exchange function of the mechanical arm, ensure the mechanical safety limiting of the limit angle of the two arms and improve the safety of the equipment.

The invention discloses a lower limb multi-joint torque intelligent prediction method and related equipment, and relates to the technical field of joint torque prediction.The method comprises the steps that original surface electromyography sEMG, kinematics data and ground reaction data of a subject under different lower limb movements are collected; kinematics data and ground reaction force data are used as input, and multi-degree-of-freedom angle data and moment data of three joints of the lower limb are obtained through inverse kinematics and inverse dynamics calculation; constructing a lower limb multi-joint torque prediction model through a deep learning technology, and performing model training by using the training set; and inputting the test sample set into the trained lower limb multi-joint torque prediction model to obtain a joint torque prediction result of the subject. According to the method, the problems of low joint torque prediction precision, high calculation cost and the like in the prior art are solved, the method has the advantages of being easy to implement, high in generalization, capable of processing large-scale data and the like, and prediction results are expected to be applied to three-dimensional compliance and modular control of the exoskeleton robot.

The invention discloses a low-power-consumption and high-precision exoskeleton body area network energy consumption management method. The method comprises the following steps: (1) constructing a three-layer heterogeneous communication architecture and initializing the three-layer heterogeneous communication architecture; (2) starting the exoskeleton robot; (3) acquiring data in real time by a sensor; (3) the control center analyzes the collected data and cooperates with the human body to complete the action, and meanwhile, the regional aggregation nodes calibrate the QoS level of the collected data; (4) the controller predicts future human motion intensity, regulates and controls a data acquisition mode, carries out dynamic QoS grading LSTM model parameter adjustment, and carries out cross-modal data alignment; (5) the QoS strategy executor calculates a comprehensive QoS label; and (6) the sensor adjusts a data transmission strategy of the sensor based on the comprehensive QoS label. According to the method, a strategy for collecting and transmitting the sensor data is adjusted based on the integrated QoS grade and the motion state, automatic network energy consumption management is carried out, and concurrent access of the sensor data is ensured while low calculation energy consumption is ensured.

The invention discloses a robot motion mode generation method and system, and the method comprises the steps: constructing an optimized adaptive CPG model, and carrying out the learning of gait signal data, and obtaining the frequency, amplitude and phase parameters; frequency, amplitude and phase parameters are input into a master-slave oscillator, and gait signals with single-joint and multi-joint coordination are generated; constructing a transition gait generation framework, and adjusting the transition weight of the gait signal through a variational controller to obtain a transition gait signal; and outputting the transition gait signal to a joint driver of the lower limb exoskeleton robot, and controlling the exoskeleton robot to execute corresponding gait actions to realize rehabilitation training of the patient. According to the invention, the dependence on the data quality and sampling rate of the sensor can be reduced, and the control precision of the joint driver is realized. The robot motion mode generation method and system can be widely applied to the technical field of robot control.

The invention relates to the technical field of medical rehabilitation instruments, and discloses an exoskeleton robot for fracture auxiliary rehabilitation. The robot comprises a shear deformation sensing assembly, a shape memory alloy locking assembly and a joint driving module. The shear deformation sensing assembly comprises a fixed shell, a flexible liner arranged on the inner side of the shell and a sensing beam connected between the shell and the liner. The shape memory alloy locking assembly comprises a locking pin arranged in the connecting rod structure, a shape memory alloy driving piece in linkage with the locking pin and a locking part located on the connecting rod structure and corresponding to the locking pin in position. And the strain gauge is electrically connected with the shape memory alloy driving piece. Transverse micro-slippage representing shearing risks is directly sensed through a mechanical structure, rigid mechanical locking is triggered in a linkage mode, and therefore rapid and reliable physical protection is provided for a fracture part, and secondary injury in rehabilitation training is effectively prevented.

The invention relates to the technical field of rehabilitation medical robots, and particularly provides a joint angle vector generation method and a gait control method.The generation method comprises the steps that a first gait phase and multi-sensor data at the current moment are obtained; the first gait phase is the gait phase of the lower limb exoskeleton robot at the previous moment, and the multi-sensor data comprises multi-modal motion data and visual data; predicting a second gait phase according to the first gait phase and the multi-modal motion data; the second gait phase is the gait phase of the lower limb exoskeleton robot at the current moment; adjusting a reference joint angle vector and a time scaling factor of a self-adaptive joint angle vector generator of which the weight is optimized in advance according to the visual data, and then generating an expected joint angle vector according to the second gait phase by utilizing the adjusted self-adaptive joint angle vector generator; according to the method, the joint angle vector which adapts to the current environment and is high in gait bionic performance can be generated.

The invention relates to the technical field of robots, and discloses a human body tumble protection method and device, an exoskeleton robot and a medium, and the method comprises the steps: obtaining multi-modal motion data, collected by a sensor in real time, of a user; inputting the multi-modal motion data into a tumble identification model for identification and classification to obtain a tumble type probability of the user; if the tumble probability is greater than a preset safety threshold, determining that the user is in a tumble trend, and generating a variable impedance control instruction matched with the target tumble type according to a preset strategy library; and determining a rigidity parameter and a damping parameter of a target joint motor according to the variable impedance control instruction, and determining a target output torque based on the joint motion data, so that the target joint motor performs fall protection on the user based on the target output torque. The fall type can be accurately recognized, flexible buffering can be achieved, and then the injury risk of a user is remarkably reduced.

This invention relates to a multi-task motion pattern recognition system and method for underwater exoskeleton robots. Through innovative data preprocessing and network architecture design, it utilizes a small amount of IMU data to synchronously, in real-time, and with high precision complete motion pattern classification and continuous motion phase prediction, thereby driving the exoskeleton to achieve precise and synchronous assisted control. The multi-task motion pattern recognition system for underwater exoskeleton robots includes a sensing module for acquiring raw posture data of a diver; a data processing module for receiving and calculating relative IMU posture data within the human coordinate system to construct an input tensor; an intent recognition module, including a multi-task deep neural network based on an inverted Transformer architecture, for receiving the input tensor and synchronously outputting motion pattern classification results and continuous motion phase prediction results; and a control module for generating control signals for the underwater exoskeleton based on the motion pattern classification results and continuous motion phase prediction results.

The invention discloses a self-adaptive admittance control method and system for a lower limb exoskeleton robot, and relates to the technical field of robot admittance control. The self-adaptive admittance control method for the lower limb exoskeleton robot comprises the following steps: acquiring man-machine interaction time sequence data and user physiological state time sequence data of the lower limb exoskeleton robot; based on the man-machine interaction time sequence data of the lower limb exoskeleton robot, analyzing a user assistance demand characteristic value of the lower limb exoskeleton robot; based on the user physiological state time sequence data of the lower limb exoskeleton robot, the user fatigue characteristic value of the lower limb exoskeleton robot is analyzed, and the admittance regulation characteristic value of the lower limb exoskeleton robot is analyzed in combination with the user assistance demand characteristic value; according to the method, the self-adaptive admittance control processing is performed on the lower limb exoskeleton robot based on the admittance regulation characteristic value, so that the admittance regulation can be automatically performed according to the movement requirement and the physiological state of the user, and the adaptability of man-machine cooperative movement is remarkably improved.

1. Name of the product in this design: Multi-degree-of-freedom foot and ankle exoskeleton. 2. Purpose of this design: for use in exoskeleton robots. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention relates to the technical field of human exoskeleton robots, and discloses an upper limb exoskeleton self-adaptive shoulder supporting structure which comprises a supporting assembly, a stacking chain assembly and an elastic reset assembly. The supporting assembly is used for connecting the waist supporting assembly. The stacking chain assembly comprises a plurality of linkage pieces, when the multiple linkage pieces are connected, the linkage shaft of the previous linkage piece is rotatably arranged in the first sleeve of the next linkage piece so that the next linkage piece can rotate around the linkage shaft of the previous linkage piece, and therefore the stacking chain assembly is formed. The first sleeve of the connecting piece located at the bottom end in the stacking chain assembly is rotationally connected with the supporting shaft of the supporting assembly, so that all the connecting pieces in the stacking chain assembly can rotate around the axis of the supporting assembly. The stacking chain assembly has the beneficial effects that the stacking chain assembly is high in flexibility, component force obstruction in the horizontal direction can be completely eliminated in the action process, self-adaptive compensation of the joint offset can be achieved, and the axes of human-machine shoulder joints are highly overlapped.

A knee joint mechanism includes a thigh support assembly, a connecting base, a shank support assembly and a locking mechanism. The thigh support assembly is fixed at a thigh of an exoskeleton robot, a first angle sensor is disposed on a hip, and power is provided from the hip. The connecting base is mounted with a second angle sensor. The locking mechanism includes a motor, a worm gear assembly, a locking member, an unlocking member, and a first limiting member. The unlocking member and the first limiting member firmly fix the locking member to maintain the thigh support assembly, the connecting base and the shank support assembly at an ergonomic angle. The motor drives the unlocking member to rotate through the worm gear assembly to realize unlocking. The second angle sensor controls the unlocking member to lock the locking block.

The application discloses a wearable flexible lower limb gravity balance exoskeleton and relates to the field of exoskeleton robots.The exoskeleton robot comprises a flexible garment, a knee joint binding mechanism, a Bowden cable transmission mechanism and a gravity balance device.The flexible garment is worn on the upper body of a human body, provides a stress anchor point for the gravity balance device and guarantees the stability of wearing.The knee joint binding mechanism is installed at the knee joint of the lower limb of the human body and connects the gravity balance device with the knee joint.The Bowden cable transmission mechanism is distributed on the front side of the thigh and provides assistance for the flexion of the hip joint.The Bowden cable transmission mechanism is connected with the knee joint binding mechanism.The gravity balance device is installed on the front side of the flexible garment and assists the flexion of the hip joint.The gravity balance mechanism is combined with the Bowden cable transmission mechanism and adopts a bionic driving mode to simulate the force line direction of the hip flexor muscle of the lower limb.The application adopts a variable stiffness design, and elastic elements and flexible mechanisms are matched with the motion change of the human body, so that the fitting degree of the exoskeleton with the human body is higher, and the assistance and safety are improved.

The invention is applicable to the field of wearable robots, and discloses a self-adaptive control method for a waist exoskeleton robot, which comprises the following steps: firstly, acquiring attitude and angular velocity information of double inertial measurement units and displacement and velocity information of each encoder; combining encoder information and an exoskeleton geometric model to calculate a posture calculation value of the waist relative to the pelvis, and calculating a first posture estimation value according to double inertial navigation information; converting the two postures into a relative attitude error, mapping the relative attitude error into a three-dimensional attitude error vector, constructing a dynamic weight matrix, and calculating a consistency residual error of the two postures; fusing the consistency residual error with at least one of the actuator tracking deviation, the stroke approximation degree and the prediction confidence coefficient to construct a risk index; and finally, according to a comparison result of the risk index and two preset threshold values, an exoskeleton control mode is adaptively switched to a normal mode, a compliant degradation mode or an output stopping mode, and the method can realize accurate posture estimation of the waist exoskeleton and full-process risk dynamic management and control.

1. Name of the product in this design: Hip-jointed walking exoskeleton robot (second generation). 2. Purpose of this design: This design is used for hip joint assistive walking and rehabilitation. 3. The key design features of this product are its overall shape. 4. The image or photograph that best illustrates the key design points: Design 1 3D view. 5. Design 1 is designated as the basic design.

The application discloses a kind of multi-source fusion perception systems for exoskeleton robot, belong to robot technical field, system includes:foot bottom pressure acquisition module, is laid in exoskeleton foot component;Inertial measurement module, is laid in exoskeleton limb bar piece;Motor feedback module, is integrated in exoskeleton driving joint;Central processing unit is connected with each module, for receiving and processing multi-source data, method includes: by foot bottom pressure dynamic threshold algorithm real-time determination gait switching point;Fusion inertial measurement data and motor feedback data, carry out limb posture solution and man-machine interaction moment estimation;Based on the redundancy check of multi-source data realizes fault monitoring and safety control.The application solves the problems of high gait recognition delay, poor environmental adaptability and insufficient man-machine interaction transparency in the prior art through deep coupling and synchronous perception of mechanical and kinematic data, and realizes accurate, robust and real-time perception of the wearer's movement intention.

According to the technical scheme, the rigid-flexible coupling self-adaptive protective shell for the exoskeleton robot comprises a flexible protective assembly and a rigid supporting assembly which are attached to each other; the rigid supporting assembly is located on the inner layer and composed of an aramid paper honeycomb core material and skin panels compounded on the two sides of the aramid paper honeycomb core material. The flexible protection assembly covers the outer surface of the rigid supporting assembly and comprises a three-dimensional spacer fabric layer loaded with shear thickening liquid and an artificial cartilage foam layer laminated on the inner side of the fabric layer; a wear-resistant skin layer is further compounded on the outer surface of the flexible protection assembly. Aiming at the three technical problems of single material performance, adaptability and vibration noise of an exoskeleton robot shell, a rigid-flexible coupled multi-layer self-adaptive protective shell structure is designed, the pain points are specifically solved through the synergistic effect of all the layers, meanwhile, the preparation method of the shell is provided, and the application of the shell to an exoskeleton robot is defined.

The application relates to an integrated joint and exoskeleton robot, the integrated joint comprising a ring motor structure, a planetary gear reducer and an output adapter connecting the two, the ring motor structure being sleeved outside the planetary gear reducer. The ring motor structure comprises a rotor connector, a first rotor assembly, a second rotor assembly and a stator assembly sandwiched between the two, the first rotor assembly and the second rotor assembly being fixedly connected through the rotor connector, so that the first rotor assembly and the second rotor assembly can synchronously rotate. The first rotor assembly, the second rotor assembly and the stator assembly are all annularly arranged outside the planetary gear reducer around the axis of the ring motor structure. The integrated joint and exoskeleton robot provided by the application solve the problems that the integration degree of the driving joint motor and the reducer is low, the structure of the transmission mechanism between the motor and the reducer is complex and heavy, and the driving joint is oversized, the torque density is too low and the performance is poor.

The wearable knee joint exoskeleton rehabilitation robot is characterized in that a first protector is provided with a first end and a second end which are arranged side by side, a second protector is also provided with a first end and a second end which are arranged side by side, and the first end of the first protector is rotationally connected with the first end of the second protector through a joint component; the joint motor module is provided with a motor stator and a motor rotor, the second end of the first protective tool is fixedly connected with the motor stator, the second end of the second protective tool is fixedly connected with the motor rotor, the joint motor module is electrically connected with the controller, and the first protective tool and the second protective tool are both of a carbon fiber material integrally-formed structure. Through the arrangement of the joint motor module, the problems that in the prior art, a knee joint power-assisted exoskeleton robot is cumbersome in design and cannot be widely applied in life are solved, and through the design of a humanoid knee joint structure, the human-machine compatibility, the energy utilization rate and the use safety are improved while the knee joint is protected.

This utility model discloses an exoskeleton robot control system that facilitates control, improves control effectiveness, and simplifies control methods. The exoskeleton robot control system includes an exoskeleton robot frame, an online acquisition system, a data processor, and an exoskeleton robot controller. The online acquisition system includes a smart bracelet, multiple patch-type IMU signal acquisition devices, and multiple patch-type electromyography (EMG) sensors. The smart bracelet is capable of detecting heart rate and blood pressure and can connect via WiFi or Bluetooth. The patch-type IMU signal acquisition devices integrate accelerometers and gyroscopes. The online acquisition system and the exoskeleton robot controller are electrically connected to the data processor. This exoskeleton robot control system improves user comfort and is suitable for controlling medical rehabilitation assistive exoskeleton robots, thus improving rehabilitation outcomes.

This invention discloses a knee joint rehabilitation method and system based on a graphene flexible sensor, relating to the field of pattern recognition. The invention includes the following steps: acquiring joint activity signals of a subject, wherein the joint activity signals are collected by a graphene flexible sensor; estimating knee joint angle data based on the subject's joint activity signals using a CurXGB model; mapping the knee joint angle data one-to-one with the angles of a video game; and having the subject complete the game through joint movements. This invention proposes a CurXGB regression algorithm that can generate more continuous prediction curves, providing rehabilitation exoskeleton robots with motion curves that better conform to human joint movements. Utilizing the characteristics of the graphene flexible sensor, it is applied to knee joint rehabilitation, achieving knee joint rehabilitation training through a graphene flexible sensor-based knee joint rehabilitation system, thereby increasing subject participation.

The invention discloses a power output suite and a wearable power-assisted robot, and relates to the technical field of exoskeleton robotics.The power output suite is applied to the wearable power-assisted robot and comprises a shell, a power assembly, a motion controller and a power battery, and the shell is provided with a containing cavity; the shell is provided with an external key and an interface used for being connected with the outside; the power assembly comprises a motor assembly and a speed reducer assembly which are located in the containing cavity. The motion controller is located in the containing cavity and connected with the motor assembly and the speed reducer assembly. The power battery is located in the containing cavity and used for providing electric energy for the power assembly and the motion controller. The power output kit is an independent module in the wearable power-assisted robot, has independent working and power-assisted capabilities, and is beneficial to improving the universality and convenience in modular combination of the wearable power-assisted robot.