124 results about "Joint spaces" patented technology

The invention provides an intelligent planning and control method and device for the motion trail of a mechanical arm, and the method comprises the steps: constructing a kinematic equation of the mechanical arm based on the kinematic parameters of the mechanical arm; the target position and the current position of a mechanical arm tail end tool are obtained; path nodes of the mechanical arm are planned based on the target position and the current position; interpolation is carried out on adjacent path nodes of the mechanical arm to obtain a movement track of the mechanical arm; and the mechanical arm is controlled to execute the mechanical arm motion trail. In the method, a plurality of interpolation functions are generally constructed in a joint space according to operation requirements and constraint conditions so as to ensure continuity and stability of joint motion parameters.

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 discloses a lens holding arm control method based on interactive surgical instrument segmentation, and belongs to the technical field of surgical robot control. Comprising the following steps: carrying out interactive segmentation on the tip of a surgical instrument in a first-frame image of a video returned by an endoscope at the tail end of an endoscope holding arm; automatically acquiring a tip mask of a surgical instrument in a video subsequent frame image through a tracking network model, and calculating a center coordinate of the tip mask; calculating the center coordinate of the ROI region of the image and the error between the center coordinate and the expected position coordinate by combining the weight of the user-defined surgical instrument; a joint space angle control quantity is obtained through a multi-task whole-body controller with priorities to carry out motion control on a lens holding arm, and errors of high-level tasks and low-level tasks are converged to be zero along with time. According to the method, any type and number of surgical instruments can be quickly and stably tracked without an additional model training process. The endoscope holding arm automatically adjusts the pose of the endoscope according to the central position of the tip of the surgical instrument so as to optimize the surgical field, and the man-machine cooperation surgical operation efficiency is improved.

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 relates to dental medicine. A method for restoring an individual's vertical dimension of occlusion taking into account their facial proportions consists in obtaining, from a frontal view of the patient's face, an image of the patient's temporomandibular region and of the outline of the face, and determining from the image of the temporomandibular region the presence of condylar displacement in the joint space and the direction of the displacement in relation to the centric position. The same image is used to determine the patient's vertical dimension of occlusion and to ascertain the angular deviation from the Ricketts angle of normal vertical dimension of occlusion. The lower jaw is then relocated by the amount of the ascertained deviation and in the direction of said deviation to the SNA-Pm line of an SNA-Xi-Pm intermaxillary angle. The current Gl-Sn-Pog facial convexity angle is then determined for subsequent adjustment of the relocation of the lower jaw, and a digital graphical model is obtained of the lower jaw with the condyles in the normalized position in the joint space and in relation to the normalized intermaxillary angle and facial convexity angle.

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 tail end control method of a modular rope-driven flexible mechanical arm, and relates to the technical field of mechanical control. A tail end control method of a modular rope-driven flexible mechanical arm comprises the steps that a first data driving model is constructed to establish a mapping relation of variables from a joint space to a task space of the mechanical arm; based on the first data driving model, a tail end pose controller of the mechanical arm is arranged, and the expected joint angular velocity of the joint space is obtained; constructing a second data driving model to establish a mapping relation of variables from a driving space to a joint space of the mechanical arm; based on the second data driving model, a joint angle controller of the mechanical arm is arranged, and the joint driving torque of the mechanical arm is obtained according to the expected joint angular speed; and the tail end of the mechanical arm is controlled through the joint driving torque. According to the embodiment of the invention, accurate and robust trajectory tracking control of the tail end of the flexible mechanical arm can be realized.

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 utility model provides an anti-collision limiting assembly and a mechanical arm. The anti-collision limiting assembly comprises a first limiting piece and a second limiting piece matched with the first limiting piece. The first limiting piece is used for being installed on a first mechanical arm body and provided with a first limiting face, the second limiting piece is used for being installed on a second mechanical arm body rotationally connected with the first mechanical arm body and provided with a second limiting face, and the second limiting face can abut against the first limiting face. And the second mechanical arm body stays at a limiting position relative to the first mechanical arm body. The first limiting piece and the second limiting piece abut against each other to limit the rotating angle of the mechanical arm, the limiting pieces are prevented from making direct contact with the surface of the mechanical arm, and the risk that the mechanical arm is damaged is reduced; in addition, the situation that the limiting structure occupies too much joint space, so that the joint space becomes small, and therefore when an operator rotates the second mechanical arm, the hands are prone to being clamped, and personal injuries are caused is avoided.

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 present invention provides a method and system for automatically interpreting the characteristics of knee joint lesions based on medical images, which relates to the field of intelligent medical detection technology. The method includes: obtaining a medical image to be interpreted; filtering the medical image to obtain a filtered image; constructing an image enhancement window, and using the image enhancement window to traverse the filtered image to perform denoising to obtain a denoised image; performing histogram equalization on the denoised image to obtain an enhanced image; based on deep learning technology, using the enhanced image to perform feature segmentation to obtain lesion characteristics; the lesion characteristics include: joint space, bone hyperplasia and sclerosis under the joint surface, osteophyte formation, bone cystic changes under the joint surface, joint deformity, etc. The present invention realizes the automatic interpretation of knee joint lesions through image processing and machine learning technology, and provides an efficient and accurate diagnostic tool.

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 utility model discloses an occipital bone axis distraction measuring device, and belongs to the field of medical instruments. The occipital bone and axis distraction measuring device comprises a moving assembly, a first distraction rod, a second distraction rod, a stabilizing assembly and a measuring piece, the first distraction rod and the second distraction rod are installed at the two ends of the moving assembly, the stabilizing assembly is installed between the first distraction rod and the second distraction rod, and the measuring piece is connected with the moving assembly, the first distraction rod or the second distraction rod. The moving assembly is used for adjusting the distance between the first distraction rod and the second distraction rod, the stabilizing assembly is used for providing supporting force for the first distraction rod and the second distraction rod, the measuring part is used for displaying the distance between the first distraction rod and the second distraction rod, and a first acting part is arranged at the end, away from the moving assembly, of the first distraction rod. A second acting part is arranged at the end, away from the moving assembly, of the second distraction rod. The joint gap of the atlantoaxial joint can be stably and accurately expanded, and the problems that in the prior art, a pair of simple expanding forceps is prone to loosening, and adjustment is not accurate are solved.

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.

A system and method configured to better identify patient-specific anatomical landmarks, measure anatomical parameters and features, and predict the patient's need for surgery within a predetermined time period. In some embodiments, the system and method is configured to predict the likelihood or risk that a patient will require total hip arthroplasty. In some embodiments, the present invention includes machine learning technology Some embodiments of the present invention include a first ML machine configured to received medical images as inputs and identify anatomical landmarks as outputs; a measurement module to measure joint space width, hip dysplasia angles, and / or leg length differential; and a second ML machine configured to receive the anatomical measurements and patient demographic data as inputs and produce a risk or likelihood that the patient will require surgery within a certain time frame.

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 present invention provides an arthroscopic joint space expansion device, comprising an upper clamp body and a lower clamp body, wherein the upper clamp body is hingedly connected to the lower clamp body, and the upper clamp body is divided into an upper clamp body inner section and an upper clamp body outer section with the hinge of the upper clamp body and the lower clamp body as the boundary, and the lower clamp body is divided into a lower clamp body inner section and a lower clamp body outer section with the hinge of the upper clamp body and the lower clamp body as the boundary, the end of the lower clamp body inner section is the tibia end, the end of the upper clamp body inner section is the femur end, and a tip is provided on the front side of the femur end of the upper clamp body. The device can enter the patient's body through an incision on the side of the knee joint under arthroscopy, and can expand the inner gap between the femur and the tibia, so as to facilitate the medial meniscus suturing operation.

The present invention provides an adaptive teleoperation method, computer device, and storage medium for narrow scenarios. The method includes motion data processing, including reading data of a first motion trajectory of a human hand, filtering the data, redirecting the first motion trajectory to convert it into a second motion trajectory in a robotic arm workspace, and interpolating and smoothing the data of the second motion trajectory after performing joint motion calculation to obtain the required motion trajectory data, which is then output to the robotic arm. The method also includes solving the robotic arm joint motion problem, including calculating inverse kinematics to convert the motion trajectory in the robotic arm workspace into multiple joint configurations in the joint space, and then screening and optimizing candidate joint configurations to obtain joint angle information for ultimately controlling the robotic arm. The present invention can achieve autonomous obstacle avoidance during teleoperation.