67 results about "Joint spaces" patented technology

The invention discloses a space manipulator impedance control method based on joint hysteresis dynamic position compensation, and belongs to the field of space robot nonlinear dynamics control. The control method comprises the following steps: constructing a flexible joint space manipulator model based on a standard dynamic model of the space manipulator; according to the flexible joint space manipulator model, a virtual torque sensing strategy is designed based on motor side sensor information, and a joint torsion torque estimated value is obtained; building a joint hysteresis model based on a Bi-LSTM mixed hysteresis modeling method fusing multi-scale memory and an attention mechanism, and training the joint hysteresis model; inputting a joint torsion moment estimation value into the trained joint hysteresis model, and estimating a joint torsion angle; based on the estimated joint torsion angle, the joint angle measured by the motor side encoder is subjected to superposition correction, and track error compensation caused by joint hysteresis is achieved.

The invention provides a training method and device for a VLA model, and relates to the technical field of intelligent robots with bodies, and the method comprises the steps that the VLA model outputs a joint angle sequence of a mechanical arm of a robot with a body based on visual input and language input; the differentiable forward kinematics module outputs a real-time pose of an end effector of the mechanical arm in a task space; based on joint space loss formed by the joint angle sequence and the joint angle in the teaching data, task space loss formed by the real-time pose and the tail end pose in the teaching data, and task space constraint loss, a multi-objective loss function is constructed, and total loss is calculated; calculating the gradient of the total loss to the joint angle sequence and the real-time pose through back propagation, and optimizing preset parameters of the VLA model; the above steps are repeatedly executed until the total loss meets the expectation, and a trained target VLA model is obtained; the technical problems that when a VLA model is trained in a joint space, the hardware coupling performance is high, and the generalization ability is insufficient are solved.

The application relates to a multi-arm mobile robot control system, which comprises a robot, each joint position of the mechanical arm of which is configured with a joint controller for driving joint movement; a robot controller for realizing the operation of joint motors according to control quantities; a joint position hard analysis unit for calculating the coordinate positions of each joint or mechanical arm in a space coordinate system to output results; and a joint space point position trajectory constraint model for forming a correction quantity of a joint and superimposing the correction quantity on an original control quantity of the joint to become a final control quantity for controlling the joint, the final control quantity being used for output to the joint controller to realize joint movement. The application provides a multi-arm mobile robot control system, which effectively realizes the cooperative control among multi-arm robots, avoids the mutual collision among mechanical arms, improves the avoidance and dynamic response speed of the mechanical arms, and improves the agility of robot actions.

The invention belongs to the technical field of robot intelligent control, provides a robot double-source joint information impedance control method and system, a medium and a robot, and aims at motion control of a 3R-configuration robot. Joint motion information including a filtering angle, a filtering angular velocity and a filtering angular acceleration is obtained, the pose and / or velocity information of the end effector is mapped to a joint space based on a kinematic model of the robot, and joint motion information including a mapping angle and a mapping angular velocity is obtained; fusing the angle and the angular velocity to obtain a fused angle and a fused angular velocity; and generating a control torque by combining the fusion angle, the fusion angular velocity and the filtering angular acceleration with a preset target impedance parameter and an expected trajectory. The angular velocity and the angular acceleration can be obtained without adding velocity and acceleration sensors on the motor, and the increase of the size, the complexity and the cost of the joint control motor is avoided.

The invention provides a robot arm motion control method, device and equipment, a robot and a medium, and relates to the technical field of sensors and robots. The method comprises the steps of predicting a singular value decomposition result of a Jacobian matrix through a deep learning model, and obtaining a direction vector set and a corresponding singular value sequence; dividing the direction vector into two subsets respectively corresponding to a non-approximate singular direction and an approximate singular direction based on the singular value sequence and a sensitivity threshold; decomposing the input vector of the expected speed on the two subsets to obtain a first direction component and a second direction component; and performing scaling processing on the second directional component, and calculating the speed of each joint in the joint space based on the first directional component and the scaled second directional component. According to the invention, stable and accurate motion control can be realized when the robot arm is close to the singular configuration, and the calculation complexity is reduced while the control effect is ensured, so that the resource occupation is reduced and the calculation efficiency is improved.

The invention relates to the technical field of medical image auxiliary diagnosis, and provides an intervertebral joint osteoarthritis image feature evaluation method based on deep learning, which can synchronously identify five types of FJOA image features such as joint space stenosis, osteophyte, hypertrophy, subchondral bone erosion and subchondral cyst, and improves the comprehensiveness and efficiency of evaluation. The nnU-Net model is adopted to perform high-precision segmentation on an intervertebral joint region, so that the positioning precision is effectively improved; by introducing a shared feature extraction network based on ResNet-18 and five parallel classification sub-networks, joint modeling of multi-scale semantic information is realized, and the recognition accuracy and generalization ability of the model are improved; according to the method, a Grad-CAM technology is combined to generate an activation thermodynamic diagram, a model interpretation basis is superposed to an original image, visual display of an evaluation result is realized, interpretability and clinical applicability of the model are enhanced, and FJOA image features in axial lumbar vertebra CT images from two central data sets can be quantitatively evaluated so as to comprehensively quantify individual FJOA image features.

The invention relates to a multi-arm mobile robot control system, which comprises a robot, and a joint controller for driving a joint to move is arranged at each joint position of a mechanical arm of the robot; the robot controller is used for enabling the joint controller to execute operation of the joint motor according to the control quantity; the joint position hard analysis unit is used for calculating the coordinate position of each joint or the mechanical arm in a space coordinate system so as to output a result; and the joint space point locus constraint model is used for forming the correction amount of the joint and superposing the correction amount to the original control amount of the joint to form the final control amount for controlling the joint, and the final control amount is used for being output to the joint controller to realize joint movement. According to the multi-arm mobile robot control system provided by the invention, cooperative control among multi-arm robots is effectively realized, mutual collision among mechanical arms is avoided, the avoidance and dynamic response speed of the mechanical arms is increased, and the flexibility of robot actions is improved.

The invention discloses a robot rigidity modeling method and system based on joint module nonlinear rigidity parameter fitting, and the method comprises the steps: modeling the torsional rigidity of a joint module, and expressing the relation between the torsional angle of the joint module and the joint torque through a cubic polynomial function; modeling a robot rigidity model, and expressing a relation between a joint space rigidity matrix and a robot tail end rigidity matrix through robot kinematics; identifying a torsion angle and a torque of a joint module, and acquiring the torque of the joint module through a torsion sensor or based on joint current identification; a static flexibility experiment is conducted, and the corresponding relation between the tail end force vector and the tail end elastic deformation vector of the robot is obtained; non-linear stiffness parameter fitting identification is carried out, and non-linear stiffness parameter identification is realized through a least square problem model; according to the method, non-linear rigidity parameter identification of the joint module is achieved, whole machine rigidity modeling is completed on the basis, and a basis is provided for rigidity compensation of a robot and improvement of positioning precision.

This application discloses an impedance control method, comprising: performing dynamic modeling to obtain a closed-form dynamic equation in joint space; obtaining an expression for the driving force based on the closed-form dynamic equation; obtaining the relationship between the rope velocity vector, rope tension vector, joint velocity vector, and joint equivalent torque based on the principle of virtual work; calculating the rope tension from the joint torque, where the driving force solution can be expressed as the sum of a least-squares solution and an arbitrary null-space solution; analyzing the joint torque output capacity under rope tension constraints; establishing an ideal mathematical model for the tension transmission process of the rope-driven joint and analyzing the transient coupling effect under rope tension control in joint space; performing joint motion analysis under joint tension control in joint space; and establishing a target impedance model in joint space. This application effectively eliminates coupling phenomena in the tension control process and improves the active compliance of a rope-driven serpentine manipulator.

Provided are a biplanar image-based preoperative planning method and system for total knee arthroplasty. Based on a static biplanar lower-limb image of a knee joint of a target object in a standing position and a dynamic biplanar image of the knee joint during functional motion, as well as an imported three-dimensional model, functional parameters, morphological parameters, and a three-dimensional medial and lateral joint gap of the knee joint are calculated, and then iterative calculation is continuously carried out using a two-dimensional model and a three-dimensional dynamic model to obtain a dynamically optimized placement position, so that preoperative TKA prosthesis model selection for balanced joint space across full flexion angles can be achieved; meanwhile, TKA prosthesis position planning for correcting the mechanical axis of the knee joint under three-dimensional weight-bearing conditions is considered, thereby accurately restoring the real dynamic motion of a patient, and improving the prosthesis-patient matching degree.

The invention provides a mechanical arm control method and device, computer equipment and a storage medium, and the method comprises the steps that the target tail end pose and the initial joint angle of a mechanical arm are obtained; based on the target tail end pose, self-motion variables are introduced to parameterize the joint space of the mechanical arm, and multiple sets of candidate joint angles are obtained; constructing a joint motion cost function, and determining the total cost of moving from the initial joint angle to each group of candidate joint angles based on the joint motion cost function; traversing the value range of the self-motion variable, and screening out a solution with the minimum total cost from the multiple groups of candidate joint angles according to the joint motion cost function to serve as an optimal inverse kinematics solution; and a control signal is generated based on the optimal inverse kinematics solution, all joints of the mechanical arm are driven to move, and therefore the tail end of the mechanical arm reaches the target tail end pose. By the adoption of the method, the accuracy, economical efficiency and reliability of mechanical arm control can be improved.

The invention provides a virtual surgical instrument posture control method and device, a medium and a program product. The method comprises the steps that a global coordinate system of a virtual scene where a virtual surgical instrument is located is constructed; acquiring local pose information of an operation end of the main control equipment, mapping the local pose information to the global coordinate system through a coordinate transformation relation, and constructing a corresponding end point pose; on the basis of the tail end point pose, inverse kinematics solution is executed, multiple control parameters of the virtual surgical instrument are determined, and the multiple control parameters comprise target angle parameters of all joint spaces of the virtual surgical instrument, the postures of joints, the elongation of the instrument and the postures of fixed points; according to the control parameters, the virtual surgical instrument is controlled to conduct real-time posture updating in the virtual scene, so that synchronous control over the movement state of the instrument is achieved. According to the method, the unified global coordinate system is constructed, and inverse solution calculation is executed on the basis of the unified global coordinate system, so that the stability of attitude calculation is improved, and real-time updating and accurate control of the attitude of the virtual instrument are realized.

An intraoperative surgical system for knee arthroplasty may be configured and / or reconfigurable to allow the surgical system to be inserted into different sized joint spaces during a surgical procedure. For example, the surgical system may include a sensor support body defining a platform, a force sensor, and a plurality of sensor covers each being configured to be detachably attached to the sensor support body. Each of the sensor covers can vary from each other in at least one characteristic. A selected one of the sensor covers can be placed over the platform, sandwiching the force sensor between the platform and sensor cover, to define a joint insertion block configured to be inserted into a tibiofemoral joint for measuring a force between a tibia and a femur defining the tibiofemoral joint.

An approach to stabilizing the sacroiliac (SI) joint employs flexible, structurally supportive implants that adapt to the complex anatomy of the SI joint. The associated methods are less invasive and are able to navigate the complex structure of the SI joint and its surrounding muscles, ligaments, and neural network. The implants can follow the joints' natural anatomy, fill the joint space, and create an extensive fusion base to provide stability to the SI joint.

The invention discloses a flexible wiping method and system of a flexible joint space robot based on dynamic adaptive impedance control, and the method comprises the steps: firstly, building a contact model between the flexible joint space robot and a wiped target; then, self-adaptive impedance control for dynamically updating impedance parameters is designed; and finally, performing comparison simulation on classical constant impedance, fixed update rate adaptive impedance control and dynamic update rate adaptive impedance control, and verifying the effectiveness of the method combining the dynamic update rate adaptive impedance control and singular perturbation control on friction force compliance control in the wiping process of the flexible joint space manipulator by a simulation result. The method is used for the field of on-orbit wiping of the flexible joint space robot, and accurate compliance force control can be conducted on the flexible joint space robot rapidly, efficiently and accurately; when the flexible joint space robot executes a task, necessary guarantee can be provided for the flexible joint space robot, and it is ensured that the space robot and a wiping target are not damaged, and meanwhile a good cleaning effect is obtained.

The invention discloses a gait analysis device and method based on infrared data and video influence data. The method specifically comprises the following steps: synchronously obtaining front gait video data, side gait video data and infrared image data of a target to be detected; based on the front gait video data, image preprocessing is executed, key points are detected, and then the knee joint introversion angle, the foot rotation angle, the trunk roll amplitude and the step width of the to-be-detected target are calculated according to the key points to obtain the knee joint introversion angle, the foot rotation angle, the trunk roll amplitude and the step width of the to-be-detected target. Meanwhile, the human body posture is obtained based on the front gait video data and the side gait video data, the joint space coordinates are constructed based on the infrared image data, and the human body posture is put into the joint space coordinates for cross validation so as to ensure the accuracy of the obtained various parameters. Through fusion of multi-dimensional data, gait features can be reflected more comprehensively, and a comprehensive and accurate gait analysis result is finally generated through integration.

The invention discloses a characterization method for describing tibia malformation correction path features, and the characterization method comprises the following steps: S1, building a bone section model, and modeling a bone section after osteotomy into a closed ring surface with the tail end of the bone section as the center; s2, according to the total correction period, the total adjustment amount of all traction rods of the parallel external fixator is averagely distributed every day, and then joint space equal-interval discrete planning is achieved; s3, constructing correction path characteristic evaluation indexes including rod length adjustment rate, bone section position stretching rate and bone section posture stretching speed; s4, the new bone shape is visually represented, the growth process of the bone section is represented as a series of discrete closed ring surfaces along the correction path, and the new bone shape is represented as the volume swept by the series of discrete closed ring surfaces along the correction path. According to the method, the visual representation of the new bone generation process in the malformation correction process is realized, so that a clinician is assisted to carry out feasibility analysis and evaluation on a preoperative correction prescription.

The invention discloses a knee joint force line adjusting system and method based on intelligent feedback control, and relates to the technical field of medical rehabilitation instruments. The system comprises an overall control and man-machine interaction end, a correction device sensor end and a correction device hardware platform end. The hardware platform end comprises a joint force applying module and a thigh and shank multi-degree-of-freedom motion module; the sensor end is used for detecting joint pressure and lower limb force line state in real time. On the basis of traditional three-point type orthopedics, the applied force is adjusted through the control module according to real-time feedback, and the shank is matched for synchronous stretching and rotating movement, so that the knee joint force line is dynamically adjusted. In addition, the system combines multi-modal data, constructs a closed-loop decision model by using deep learning and large model reasoning technologies, and outputs correction effect evaluation and next training parameter recommendation. The digital and intelligent knee joint correction system realizes digitization and intelligentization of knee joint correction, can effectively enlarge joint gaps, improves stress distribution, and provides a personalized and safe rehabilitation treatment scheme for middle-aged and elderly osteoarthritis patients.

The application discloses a flexible joint space robot fast impedance control method based on contact torque compensation, first determines a state space equation of the flexible joint space robot based on a dynamic model of the flexible joint space robot, then sequentially constructs a contact torque compensator, an expected impedance model and a fixed time disturbance observer, determines compensated contact torque, impedance error intermediate value and external disturbance, then constructs a finite time impedance controller according to a singularity avoidance auxiliary function and auxiliary system state quantity, determines actual input torque of the space robot, and completes impedance control on the flexible joint space robot. The technical scheme of the application can improve the robustness of the control system, can solve the input saturation problem that may occur in the control process, can make the impedance error quickly converge, can effectively overcome the influence of external disturbance and input saturation, and improves the control precision of the contact force.

The application belongs to the technical field of robot intelligent control, and provides a robot dual-source joint information impedance control method, system, medium and robot, which is oriented to the motion control of a 3R configuration robot, and comprises the following steps: performing signal filtering and differential processing on original motion state data of each joint of the robot to obtain joint motion information including filtered angle, filtered angular velocity and filtered angular acceleration; based on a kinematics model of the robot, mapping pose and / or velocity information of an end effector to a joint space to obtain mapping angle and mapping angular velocity; respectively fusing the angle and the angular velocity to obtain fused angle and fused angular velocity; and generating a control torque by combining the fused angle, the fused angular velocity and the filtered angular acceleration with preset target impedance parameters and an expected trajectory. According to the application, the angular velocity and the angular acceleration can be obtained without adding speed and acceleration sensors on the motor, so that the size, complexity and cost of the joint control motor are avoided.

The invention relates to an articulated robotic arm device with a neural-network system for movement of a robotic arm, the neural-network system being capable of learning online and in real time the forces for moving its joints towards a target position by simulation of virtual springs implementing impedance control, wherein learning the rest elongations of the virtual springs for a selected state defines the equilibrium position of the arm corresponding to a zero resultant of the forces applied to the arm, thereby giving the arm elasticity properties as a function of the stiffness selected for the springs, at equilibrium, wherein the neural network learns these elongations for each transition from one target position to another target position in the joint space, making it possible to control movement of the arm in order to learn a sequence of movements and define the behavior of the arm for a given task, each joint of the arm having a target position.

The application relates to an environment perception-based mechanical arm obstacle avoidance trajectory planning method and system, which comprises the following steps: acquiring joint angle data and end effector position data of a mechanical arm, establishing a joint space for mechanical arm work according to the joint angle data and the end effector position data; acquiring environment point cloud data, extracting obstacle information based on the environment point cloud data, and acquiring a safe operation space of the mechanical arm through the obstacle information; acquiring a current joint angle combination of the mechanical arm, converting a position difference between the current joint angle combination and a target position into an angle increment in the joint space, and adjusting an angle value exceeding the boundary of the safe operation space, so as to complete obstacle avoidance trajectory planning of the mechanical arm. The application can realize a grabbing task while avoiding obstacles.

The application relates to a robot motion trajectory determination method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring a given joint position waypoint, determining a first transition waypoint between a current joint position waypoint and a previous joint position waypoint, determining a second transition waypoint between the current joint position waypoint and a next joint position waypoint; creating a joint position spline path according to the given joint position waypoint, the first transition waypoint and the second transition waypoint; taking the shortest time through the joint position spline path as a target, taking joint space constraint conditions and Cartesian space constraint conditions as constraints, obtaining a relationship between path parameters of the joint position spline path and time; and obtaining joint position trajectory planning of the robot according to the relationship between the path parameters of the joint position spline path and the time. The method can improve the operation efficiency of the robot.

The application provides a Bessel curve posture interpolation trajectory optimization method, system and computer device, a mapping relationship between a posture trajectory in a Cartesian space and a Lie algebra space tangent vector is established, a Bessel curve interpolation trajectory in the Lie algebra space is constructed, and based on a curvature radius change model and a speed change model of the Bessel curve interpolation trajectory, the smoothness and stability of a multi-section posture interpolation trajectory when a rotation axis changes are improved. Furthermore, based on a Jacobian matrix mapping of a mechanical arm joint space and the Cartesian space, a joint space speed constraint is added, and a joint space maximum angular velocity constraint problem of the mechanical arm is considered to further constrain the Cartesian space speed, bidirectional feedback of the joint space and the Cartesian space is realized, the stability of each joint motion of the mechanical arm is improved, the speed curve of each joint of the mechanical arm is continuous, and the precision of the mechanical arm trajectory tracking is improved.

The invention discloses a total knee arthroplasty demand prediction method and system, and relates to the field of clinical auxiliary decision making. The method comprises the following steps: acquiring a knee MRI image, and automatically segmenting a joint gap key structure through a deep convolutional neural network to obtain a volume of interest (VOI); using an SERA tool to extract iconomics characteristics of the IBSI standard; and finally constructing a joint space and clinical feature radiomics model (JSC-RM) by combining a knee osteoarthritis outcome investigation (KOOS) score, so as to predict whether the TKR is accepted or not in the future 1-4 years. According to the method, LASSO feature screening and superficial layer neural network modeling are adopted, a threshold value is set in combination with a Youden index, the prediction performance is superior to that of an existing model, the consistency and accuracy of TKR opportunity judgment of resident doctors are remarkably improved, and preoperative intelligent risk intervention is achieved.

The embodiment of the invention provides a redundant joint control method and device, equipment and a medium. The method comprises the following steps: acquiring tail end position data corresponding to a tail end position influenced by redundant joint movement in a joint space; determining an obstacle avoidance track of the redundant joint based on the tail end position data, and determining a speed function corresponding to the obstacle avoidance track; determining a constraint condition set corresponding to the speed function, and optimizing the speed function based on the constraint condition set to obtain an optimized speed function; and a control strategy of the redundant joints is determined based on the optimized speed function, and the redundant joints are driven to move based on the control strategy. According to the method, the redundant joints can accurately avoid obstacles in a complex environment, and safe, stable and efficient movement can be achieved.

In some examples, a method for preparing one or more bones involves inserting a spacer into a space defined between a first bone and a second bone, such as a joint space between a first metatarsal and medial cuneiform. A bone preparation guide can be aligned with opposed ends of the first bone and the second bone using the spacer as an alignment reference. For example, the bone preparation guide may include an opening such that the guide can be installed across the joint space with the spacer received in the opening. A clinician may use the bone preparation guide to guide a tissue removing instrument to cut or otherwise prepare the ends of the first bone portion and second bone portion.

The invention discloses a man-machine collaborative robot anisotropic admittance control method based on an offline muscle-bone performance model. Aiming at the bottleneck that the existing admittance control neglects the biomechanical heterogeneity of a human body and the inverse dynamics calculation is time-consuming, the invention constructs a control framework of offline model construction-online real-time estimation. The method comprises the following steps: establishing a human body muscle-bone model offline, performing simulation calculation on a muscle-bone force ellipsoid in a full operation space, and training a deep neural network to establish mapping from a joint space to mechanical properties; the real posture of the human body is calculated through online fusion of vision and foot motion data; and calculating the matching degree of the interaction force and the ellipsoid main shaft, and constructing a direction-dependent anisotropic admittance controller. The impedance characteristic of the robot and the human muscle-bone performance space are isomorphic, high stability in the dominant force application direction and high compliance assistance in the vulnerable direction are achieved, and the muscle-bone injury risk of an operator is effectively reduced.

Systems and methods for planning and assisting orthopaedic surgical procedures include a computer system and a robotic surgical device. The computer system receives a set of target joint space values including a target extension space value and a target flexion space value. The computer system initializes a surgical plan including planned resection heights and determines a set of current joint space values based on the surgical plan. The computer system adjusts one or more planned resection heights of the surgical plan until the set of current joint space values matches the set of target joint space values. The computer system may control the robotic surgical device according to the surgical plan.

This application belongs to the field of medical devices and protective equipment, specifically involving a design method and layered structure for an enhanced mouthguard based on musculoskeletal stability optimization. The method includes: collecting multimodal data such as the full dentition morphology, jawbone structure, mandibular movement trajectory, surface electromyography, and plantar pressure of the subject; constructing a correlation system between mandibular position and overall stability using a radial basis function neural network; setting anatomical boundaries, joint spaces, and muscle symmetry constraints; and using a genetic algorithm to iteratively optimize and lock in a personalized musculoskeletal stability position; based on this, performing layered digital design of the mouthguard's flexible base layer and posterior tooth retention components, and then 3D printing manufacturing. This application, through precise optimization of jaw position, achieves a leap from passive protection to actively enhancing body stability in sports mouthguards, significantly improving exercise efficiency and wearing comfort while ensuring physical protection.