369 results about "Kinematics" patented technology

A method for predicting and assessing motion of a user in an environment. The method includes determining estimated positions of key points of the user at a first time and determining link lengths for linkages connecting the key points. The method further includes determining, for an upcoming time, predicted positions of the key points and predicted kinematics for the key points. The estimated positions, predicted positions, and kinematics are determined periodically over a time period. The method further includes classifying an activity being performed by the user over the time period and predicting a future motion path of the user for an upcoming time period. The method further includes generating a motion assessment for the user using the predicted future motion of the user and making the motion assessment available to a device or account associated with the user.

The invention relates to a curved surface contour analysis method and related equipment for laser multi-axis linkage machining, and the method comprises the following steps: carrying out the curved surface reconstruction of a target curved surface workpiece based on a three-dimensional point cloud data set, and obtaining a digital curved surface model; performing shape analysis on the digital curved surface model to obtain a curved surface feature descriptor, and if the curved surface feature descriptor does not meet an expected geometric characteristic standard, performing spectral decomposition on the digital curved surface model based on the curved surface feature descriptor to obtain a contour feature spectrum; performing path planning on the contour characteristic spectrum based on a geodesic theory to obtain a processing track sequence; and performing kinematics solution on the processing track sequence to obtain linkage control parameters of each axis, and adjusting the linkage control parameters of each axis based on the expected geometric characteristic standard, thereby solving the technical problem that the processed curved surface workpiece cannot reach the expected geometric characteristic standard due to lack of an effective curved surface contour analysis method.

The invention relates to the technical field of dynamic weighing, and discloses an intelligent load prediction and adjustment method in a dynamic weighing system, which comprises the following steps of: separating a weighing signal into a space domain static load characteristic (pressure point distribution sparsity and gravity center geometric vector) and a time domain dynamic inertial interference component (acceleration coupling noise) through space-time double-domain decoupling; the frequency spectrum aliasing problem of a traditional filtering algorithm is eliminated from a signal source; the future interference trend is predicted based on the real-time motion state of the carrier, a feed-forward compensation signal is generated through a pre-training dynamic basis function library, and dynamic errors are actively counteracted; in combination with sensor array space consistency detection and lightweight online learning, decoupling model parameters are dynamically corrected. According to the method, space geometric analysis and kinematics feedforward prediction are combined, a traditional signal processing framework is strided out, error source separation and real-time compensation are achieved, and the dynamic weighing precision of transient working conditions such as sudden stop and speed change is remarkably improved.

The invention discloses an interferometer error calibration method and device and a computer readable storage medium, and belongs to the technical field of measurement equipment.The method comprises the steps that measurement data collected when an interferometer moves on the x / y axis of a motion table is obtained, and x / y axis compensation amount is generated through calculation processing; meanwhile, a coordinate system transformation matrix is established and optimized by using data of a marking plate arranged on a motion table, and x-axis and y-axis non-orthogonal parameters are obtained. And then the compensation amount and the non-orthogonal parameters are input into a preset kinematic model, and the accurate position of the motion platform under the global coordinate system is calculated in real time. And when a preset updating condition is met, dynamically updating the error compensation value of the interferometer through the deviation between the actual position detected by the visual system and the calculated position. Reflector surface type error compensation and non-orthogonal parameter correction are fused, and high-precision error compensation calibration of the interferometer is achieved.

The invention discloses a wind power unmanned ship path tracking control method based on active disturbance rejection linear quadratic regulation control. The method comprises the following steps: building kinematics and dynamics models based on a ship body physical structure and a system parameter identification method; according to the method, a linear quadratic regulator (LQR) is introduced into an active disturbance rejection control framework, and the strong disturbance compensation capability of the ADRC and the control accuracy of the LQR are combined; an unmanned ship guidance system is constructed based on the model, a dynamic curvature navigation control (DCNC) algorithm is adopted to dynamically adjust the navigational speed, and path tracking is ensured by controlling the course angle. The method for calculating the weight proportion of the LQR coefficient in real time overcomes the system instability caused by environment change in actual engineering application to a certain extent; the ADRC control strategy adopted by the invention effectively improves the robustness and optimality of the system.

The invention relates to a motion control method and system of a four-point support POGO column parallel mechanism. The method comprises the following steps: constructing a kinematics calculation model of the four-point support POGO column parallel mechanism; the workpiece pose, needing to be adjusted, of the workpiece is confirmed, and workpiece pose data are generated according to the workpiece pose; substituting the workpiece pose data into the kinematics calculation model to obtain pose adjustment parameter data; a parallel mechanism adjusting signal is generated according to the pose adjusting parameter data; adjusting the pose of the four-point support POGO column parallel mechanism by using the parallel mechanism adjusting signal; the motion control method of the four-point supporting POGO column parallel mechanism has the advantages of being high in control precision, fast in posture adjusting response and the like.

The invention relates to an automatic guided vehicle (AGV) adaptive path tracking method based on MPC. The method comprises the following steps: S1, establishing a kinematic discretization error model based on the kinematic characteristics of the two-wheel differential AGV, processing a continuous kinematic equation by adopting an Euler discretization method, expressing a dynamic change relationship between a transverse deviation distance and an angle deviation in a state-space equation form, and generating a kinematic discrete state-space model; the method has the advantages that the continuous equation is processed by establishing the kinematics discretization error model and adopting the Euler discretization method, the deviation dynamic relation is expressed through the state space, the calculation process is simplified, the precision is kept, sensor data are fused, the wheel type odometer, IMU and laser data are integrated through the extended Kalman filtering algorithm, and the precision is improved. The real-time position and angle deviation are calculated, the positioning accuracy is improved, a model prediction controller objective function is designed, a weight matrix and boundary constraint are introduced according to constraint conditions, and the effect of obstacle avoidance constraint is combined.

The invention discloses a design method of a multi-constraint guidance law driven by a depth deterministic strategy gradient, and belongs to the technical field of missile guidance. The method comprises the following steps: S1, establishing a three-dimensional relative kinematics model of a missile interception target; s2, based on the S1, designing a fractional order sliding mode control law and analyzing the stability of the fractional order sliding mode control law; s3, designing and optimizing an A3DPG algorithm; and S4, inducing a strategy network to learn an action strategy through a reward mechanism in a dynamic environment, and realizing a multi-constraint guidance law with shortest time, small miss distance, field of view FOV constraint, acceleration change suppression, sliding mode surface convergence reward, end attack angle constraint and total reward. According to the method, the guidance law with the convergent line-of-sight angle is designed by using the fractional order sliding mode theory, and then the sliding mode surface parameters and the reaching law parameters are dynamically learned by using the reinforcement learning algorithm, so that the guidance law with dynamic adjustment is realized. And inducing a strategy network to learn an optimal guidance law under the evaluation of the indexes through factors such as a reward mechanism in a dynamic environment.

The invention relates to a dynamic path planning method in a PFC-DWA complex environment based on an improved DWA algorithm, and belongs to the technical field of intelligent driving. The method is a window reduction algorithm for dynamic prediction in an environment with a large scene change rate. According to the algorithm, the kinematics constraint of the Ackerman steering trolley is considered, a dynamic obstacle collision evaluation window reduction strategy according to the dynamic obstacle and intelligent vehicle motion state information is provided, the dynamic window range is optimized through the motion state information and a kinematics constraint equation by using an analytic geometry method, and the dynamic obstacle avoidance capability of the intelligent vehicle is improved. In order to solve the problem that the evaluation function of the DWA algorithm lacks evaluation of the obstacle state change trend, the proposed algorithm predicts the future position information of the obstacle based on the least square method according to the historical position information of the obstacle, the future position information is fused into the evaluation function of the algorithm, and the evaluation performance of the algorithm on the simulated trajectory in the dynamic environment is improved. The problem of low arrival rate of a path planned by a conventional algorithm in a frequent scene change environment is solved.

The invention relates to the technical field of magnetic suspension conveying lines, in particular to a variable curvature trajectory prediction control method and system for a magnetic suspension conveying line and a storage medium. The method comprises the steps that a variable-curvature trajectory prediction model of the magnetic suspension conveying line is established, and the variable-curvature trajectory prediction model describes the dynamic behavior of a conveying carrier on a variable-curvature path through a kinematics equation and geometric constraints and is used for predicting trajectory deviation in real time. According to the invention, by constructing a variable curvature trajectory prediction model and a multi-target rolling optimization control system, the problems of trajectory tracking and suspension stabilization of a magnetic suspension carrier under a complex path are systematically solved. The method has the advantages that a time domain motion equation is mapped to a space domain path coordinate system based on a curve coordinate system of arc length parameterization and a prediction model constructed by a French-Serret formula, the influence of curvature change on lateral displacement dynamics is accurately described, and dynamics mismatch caused by traditional fixed curvature approximation is eliminated from the model level.

The invention discloses a mechanical arm repetitive motion inverse solution solving method and system considering iteration initial value selection. The problems that when a mechanical arm inverse solution is solved through a numerical iteration method based on a Jacobian matrix, dependence on iteration initial value selection is high, and motion cannot be repeated are solved. Comprising the steps that an accurate reachable working space of the mechanical arm is obtained, a certain number of reference inverse solutions optimized through an operability index are additionally stored in the accurate reachable working space, and an enhanced reachable working space is obtained; according to the expected pose information of the mechanical arm and the enhanced reachable working space, an iteration initial value for solving the inverse solution of the pose is selected and obtained; acquiring a tail end pose error kinematical equation of the mechanical arm at a joint position layer, and deducing to obtain an iterative updating equation of a joint position; and a repeatable motion index function is designed, a joint position iteration updating equation with the repeatable motion function is obtained, and according to the iteration updating equation and the selected iteration initial value, a mechanical arm repeated motion inverse solution solving scheme selected by considering the iteration initial value is obtained.

The invention discloses a satellite attitude system anti-interference finite time control method under complex dynamic disturbance, and the method comprises the steps: building a rigid satellite attitude maneuver control model according to satellite attitude dynamics and kinematics equations; designing a self-adaptive fine disturbance observer to estimate the total disturbance of a satellite attitude system by combining the influence of the external disturbance variable on the rigid satellite attitude maneuver process, and outputting an estimated value of the external disturbance variable; a three-stage segmented sliding mode control method is designed, dynamic continuity of a three-stage sliding mode is ensured, and segmented sliding mode control output is obtained; and compensating the segmented sliding mode control output by using an estimated value of an external disturbance variable output by a self-adaptive fine disturbance observer to realize satellite attitude stable control. According to the method, the problem that the stability of the satellite is reduced in the attitude maneuvering performance process when external disturbance exists is solved, better observation performance and shorter attitude stabilization time are achieved, and the control precision of the satellite is effectively improved.

The invention provides a space target trajectory parallel mapping method based on a physical information network, and belongs to the field of time sequence data processing in deep learning. Aiming at the problems that a large amount of repetitive work exists and time and labor are consumed in the process of space target motion physical system analysis modeling and accumulative error correction, the method comprises the steps of fitting a kinematics equation of a space target in a parallel digital space through a parameterized neural network, and introducing known physical equation information; and the constraint network searches an optimal hypothesis process in a hypothesis space, and a parallel space modeling mapping process is converted into solution of a parameter inversion problem in a target domain, so that rapid construction of a parallel digital space is realized. Meanwhile, along with the increase of input sample data, the ability of the cross-cycle space-time attention module designed by the method for capturing the motion characteristics of the space target is stronger and stronger, and dynamic correction of errors is realized in a continuous iteration process.

The invention discloses a parallel six-degree-of-freedom platform pose control method based on a PSO-GA method, and the method comprises the following steps: S1, simplifying a six-degree-of-freedom platform model, and facilitating the mathematical modeling; s2, constructing a target function according to the six-degree-of-freedom platform structure parameters; s3, solving an objective function by using a PSO-GA method; s4, according to the solution of the objective function and the geometrical relationship of the six-degree-of-freedom platform, the platform pose is obtained; and S5, a position servo controller is designed, the difference between the pose obtained through the positive solution and the given pose is obtained and input to the position controller, and the rod length of each rod of the six-degree-of-freedom platform is controlled. The invention provides a kinematics algorithm capable of quickly solving the platform position and realizing stable control so as to realize quick and stable control on the parallel platform.

The invention discloses a large ship autonomous berthing path planning method, and relates to the technical field of channel control. The method comprises the steps of collecting and processing data, establishing a ship motion model, setting a path planning target, selecting and solving an optimization algorithm, verifying and adjusting a path, obtaining hydro meteorological historical data and real-time sensing data of port wind, wave and flow, ship basic parameters and under-actuated dynamic characteristic data, and preprocessing the data. Obtaining a ship motion model; minimum berthing time, minimum energy consumption and maximum safety are set, and a comprehensive objective function is obtained; defining constraint conditions of kinematics, dynamics, port environment and collision avoidance; solving by using an optimization algorithm, performing dynamics simulation verification and collision detection verification on the planned path, adjusting parameters of the optimization algorithm, and modifying a target function or a constraint condition; according to the method, the optimal berthing path can be planned, the collision risk is effectively avoided, the safety and efficiency of large ship berthing are improved, and the method has universality and flexibility.

The invention discloses a self-adaptive recognition method and system based on a four-bar linkage single station machine motion trail, and belongs to the technical field of motion trail recognition. The method comprises the following steps: acquiring a multi-source synchronous data stream, detecting a peak interference frequency, adjusting an adaptive notch filter in real time, obtaining a pure geomagnetic field signal, calculating the equivalent length of a connecting rod by using angle and force data, and establishing a kinematics equation to solve track coordinates; establishing a magnetic field space gradient tensor model through a magnetometer array, fitting a nonlinear mapping relation between an angle and a gradient tensor, and generating a metal magnetic interference compensation model; judging a motion mode and dynamically adjusting filter parameters; constructing a fast and slow dual-time scale filter to fuse multi-source information, and introducing a fading factor to prevent divergence; a future angle is predicted by using a long-short-term memory neural network to serve as a virtual observed quantity to enhance the fault-tolerant capability; and optimizing the reconstruction trajectory through multiple physical constraints. According to the method, the track identification precision, the anti-interference capability and the system robustness are remarkably improved.

The invention provides a spindle radial rotation error separation method based on a multi-point method. The spindle radial rotation error separation method comprises the steps that firstly, displacement data of a spindle are collected through a first directional displacement sensor and a second directional displacement sensor; step 2, inputting displacement data into an error separation model, and outputting a forward rotation error and a backward rotation error; wherein the establishment of the error separation model comprises the following steps: (1) based on kinematics analysis of a main shaft, establishing measurement data of a main shaft radial rotation error test model to obtain a direction displacement error measurement model and a direction displacement error measurement model; and (2) eliminating a sensor installation offset error and a test rod roundness error based on an improved multi-point error separation method to obtain a pure spindle radial rotation error. According to the invention, on the basis of eliminating the offset error of sensor installation and the roundness error of the test detection rod in the measurement data, the pure spindle radial rotation error is obtained, and the high-precision measurement of the spindle radial rotation error is realized.

The invention relates to the technical field of unmanned system multi-agent control, in particular to a wheel type mobile mechanical arm coordination control method, system and device. Comprising the following steps that a wheeled mobile mechanical arm model is established, and a target reachability area is solved; the operability index of the wheeled mobile mechanical arm is calculated; calculating the maximum linear velocity and angular velocity of the wheel type mobile mechanical arm to obtain a velocity ellipsoid model of the wheel type mobile mechanical arm; designing a multi-agent combined state space, and designing a multi-agent combined action space; constructing a control algorithm flow; setting a task scene of a coordination control algorithm of the wheeled mobile manipulator, setting training hyper-parameters, and designing task evaluation indexes; and carrying out training setting, and recording the success rate of the task and the validity of the process when the training period is finished. According to the method, the problem that the model structure is complex and depends on kinematics equation solving or objective function optimization under the high-dimensional condition is solved. According to the invention, the technical effect of reducing complexity calculation is achieved.

The invention discloses an event-triggered unmanned underwater vehicle model prediction control method, which can effectively reduce the calculation cost while ensuring the trajectory tracking performance by executing the motion and path planning of a UUV (Unmanned Underwater Vehicle) at different frequencies. When a trajectory tracking error reaches a preset threshold value or the UUV approaches a target trajectory end point, the system triggers generation of a new reference trajectory, so that the adaptability of path tracking is improved. According to the event triggering MPC algorithm, kinematics and dynamics models of the UUV are combined, it is ensured that a controller can accurately track a feasible reference trajectory, and therefore the gap between motion planning and control is effectively bridged.

The invention provides a microlens array turning motion trail optimization method and device and a medium, and relates to the technical field of microlens array turning motion trail optimizing.The method comprises the steps that a continuous trail curve P (u) is constructed based on discrete tool path points corresponding to the microlens array turning process; dispersing the P (u) into a plurality of track points in a parameter domain to obtain a track point list G; sequentially determining the forward maximum feasible parameter speed of each track point from the forward first track point; starting from the first reverse track point, determining the reverse maximum feasible parameter speed of each track point in sequence; determining the target maximum feasible parameter speed of the corresponding track point; according to the target maximum feasible parameter speed of each track point in the G, generating an optimal track which corresponds to the P (u) and meets kinematics constraints; according to the method, the optimization process of the parameter speed can be simplified, the number of trial and error iterations is reduced, the calculation complexity is reduced, and the calculation efficiency of trajectory optimization is remarkably improved.

The invention provides an automatic calibration method and device for a mechanical arm, electronic equipment and a storage medium, and the method comprises the steps that the mechanical arm is controlled to conduct RCM motion in the Y-Z axis direction, and the pitch angle range is determined; performing multiple RCM rotation sampling in the pitch angle range, and determining a motion deviation error of each rotation position point based on the Y-axis unit pixel actual distance, the first needle point pixel coordinate, the first space point coordinate, and the second needle point pixel coordinate and the second space point coordinate of the rotation position point under each RCM rotation sampling; determining a calibration matrix based on the motor position of each rotation position point and a forward kinematics equation of the mechanical arm; and least square method processing is conducted on the multiple motion deviation errors and the calibration matrix, and the calibration amount of the to-be-calibrated parameters of the mechanical arm in the YZ axis calibration direction is determined. The device is low in cost, low in calibration time consumption, high in calibration accuracy and automatic, and factory calibration of the mechanical arms can be carried out on a large scale.

The invention discloses a whole body attitude estimation method based on a sparse inertial sensor. The method comprises the following steps: 1, synthesizing acceleration data, direction data and angular velocity data through a finite difference method and a forward kinematics algorithm; 2, performing alignment processing on original acceleration data and original direction data acquired by three inertial sensors worn on a head joint, a left wrist joint and a right wrist joint of the user by rotating the transformation matrix; and 3, extracting depth features of an inertial motion data sample through an encoder combining Transform Encoder and a bidirectional long-short time memory network, designing a decoder based on a multilayer perceptron to calculate positions and relative rotation of joints, and sequentially estimating the relative rotation of the joints of different parts in a plurality of stages in combination with a human body kinematics model so as to realize whole body posture estimation. The method can effectively overcome the defect that sparse inertia input is used for whole body motion reconstruction in an existing attitude estimation method, and the robustness and prediction precision of the system are effectively improved.

The invention relates to an optimal fault-tolerant control method and system for coastal tugboat robust path tracking. The method comprises the steps of establishing three-degree-of-freedom tugboat kinematics and dynamics equations, constructing an error system which considers external ocean disturbance and internal propeller faults at the same time according to information of a reference trajectory, constructing a proper discount performance function in combination with the error system, and calculating the discount performance of the tugboat according to the discount performance function. Wherein the discount performance function comprises estimation for external ocean disturbance and internal thruster faults, and an optimal solution of the discount performance function is obtained through de-iterative optimization of an action home-approval home neural network based on an adaptive dynamic programming method. According to the method, tugboat path tracking control under the multi-constraint condition can be overcome, and the parameter setting process is simplified.

The invention discloses a parameterized design method for a flapping wing device, which belongs to the field of aerospace and comprises the following steps: determining the flapping amplitude of a designed flapping wing mechanism; according to the relation between all rods and angles in the crank sliding block mechanism, the transition mechanism and the swing guide rod mechanism, the relation between the angular speed # imgabs 1 # of a crank # imgabs 0 # rotating around the circle center in the crank sliding block mechanism and the angular speed # imgabs 3 # of a first guide rod # imgabs 2 # in the swing guide rod mechanism is determined; the rod length of each mechanism is obtained through the upper limit position, the middle position and the lower limit position of the mechanism. According to the parameterization design method for the flapping wing device, the flapping wing mechanism is obtained through rule derivation between geometric dimensions and kinematics, large flapping amplitude can be achieved, and thoughts are provided for design of the flapping wing mechanism.

The invention provides a modeling simulation method for a digital twin model of a fixed-wing unmanned aerial vehicle, and relates to the technical field of digital twin. The method comprises the following steps: establishing a fixed-wing unmanned aerial vehicle three-dimensional model Establishing dynamics and kinematics equations of the fixed-wing unmanned aerial vehicle; deducing a linear model of the fixed-wing unmanned aerial vehicle and an actuator fault model; establishing a digital twinborn model of the fixed-wing unmanned aerial vehicle; establishing a real-time communication relation between the fixed-wing unmanned aerial vehicle digital twin model and the entity fixed-wing unmanned aerial vehicle model; and operating the digital twin model of the fixed-wing unmanned aerial vehicle for simulation, and outputting flight state data in a visual interface. The method has the characteristics of high synchronism and coordination of the equipment entity and the equipment model, and the purposes of comprehensively controlling the actual operation state of the equipment and establishing the digital twin model of the fixed-wing unmanned aerial vehicle can be achieved.

The embodiment of the invention discloses a moving body track planning method and device, electronic equipment and a storage medium, and relates to the technical field of track planning, and the method comprises the steps: carrying out the geometric boundary expansion and minimum distance detection of a moving body, and obtaining the environment complexity of a starting point and an end point of the moving body, the method comprises the steps of obtaining an initial trajectory and constructing kinematic constraints based on a mixed A * algorithm of a bidirectional search strategy, constructing a safety corridor based on the initial trajectory to obtain obstacle avoidance constraints, calculating environment complexity of each trajectory point according to the safety corridor, classifying the trajectory points to obtain sampling time constraints, and obtaining final constraints according to the constraints. Using the initial trajectory as an initial solution to obtain a planned trajectory, performing transverse and longitudinal decoupling on the planned trajectory to respectively obtain transverse and longitudinal state equations, and performing tracking control on the moving body by adopting a model predictive control (MPC) algorithm. According to the method, the problems of low calculation efficiency, infeasible trajectory planning result and poor optimization process convergence in the prior art are solved.

The invention discloses a traffic safety risk early warning method and system based on intersection traffic flow information, and relates to the technical field of traffic safety monitoring, and the method comprises the steps: dividing an intersection region into space-time grids, generating a pixel-level optical flow field through a minimization energy function, converting the pixel-level optical flow field into a physical optical flow field, and carrying out the early warning of the traffic safety risk based on the physical optical flow field. Mapping the physical optical flow field to a space-time grid, and fusing the average optical flow vector and the velocity vector through a least square method to generate a fused velocity vector; predicting the future trajectory of each vehicle based on a kinematic equation, generating a grid risk by integrating the traffic flow density, the normalized grid confusion degree and the optimized strategy probability vector, and calculating the overall risk of the intersection through weighted average; and carrying out risk early warning on the overall risk of the intersection. According to the method, optical flow field analysis is combined with velocity vector fusion, the representation precision of the motion state of the vehicle is improved, kinematics prediction is combined with trajectory intersection analysis, and the capability of finding potential collision risks in advance is improved.

The invention relates to a self-adaptive fault-tolerant generalization control method for an autonomous underwater vehicle, which comprises the following steps of: considering primary and quadratic term damping effects of water, unknown constant matrixes of a mass matrix and an inertia matrix of the autonomous underwater vehicle and external interference factors; an actuator effectiveness index matrix is introduced to model the autonomous underwater vehicle into an under-actuated model, and meanwhile it is ensured that the resultant force of gravity and buoyancy is zero, and kinematics and dynamics equations of the autonomous underwater vehicle are obtained; a controller is designed based on a backstepping method, a position error and a saturation function are defined, a Lyapunov function is selected, the position error is driven to be within a preset fixed constant range, an estimation rule and a projection function are introduced for solving the problem of unknown parameters to calculate thrust and control input, and high-precision trajectory tracking control over the autonomous underwater vehicle is achieved. Compared with the prior art, the method does not need linearization or conversion dynamics, can solve the problems of fault tolerance and time-varying interference, is better in performance, and effectively improves the control precision and stability of the autonomous underwater vehicle.

The invention provides a freezing gait assessment method, device and system. The frozen gait evaluation method comprises the following steps: generating a kinematics feature set, a dynamics feature set and a space-time parameter feature set of gaits of a detected object; for each feature set, constructing an attribute graph for representing the feature set, and performing feature extraction on the attribute graph to obtain a corresponding graph feature and an importance score of each gait feature in the feature set; based on the weight value corresponding to each feature set, carrying out fusion and feature extraction on the graph features corresponding to each feature set to obtain global features; inputting the global features into a prediction module to obtain a frozen gait severity score of the detected object; and for each gait feature, determining the gait score of the gait feature based on the normalized feature value of the gait feature, the importance score and the weight value corresponding to the feature set where the gait feature is located, and generating a radar map for representing the gait mode of the detected object based on the gait scores of all the gait features.

The invention discloses a high-voltage switch operating mechanism cam optimization method and system based on a genetic algorithm, and relates to the technical field of high voltage, and the method comprises the steps: building an operating mechanism three-dimensional simulation model based on an ADAMS virtual prototype technology; performing parameter setting and boundary condition setting on the operating mechanism simulation model based on an ADAMS virtual prototype technology; performing dynamic simulation on the simulation model based on an ADAMS virtual prototype technology to obtain a stroke and speed curve of the connecting pull rod; determining a design variable, a target function and a constraint condition of a genetic algorithm based on a high-degree polynomial to obtain an optimized mathematical model of the cam mechanism; and outputting the optimal structure parameters of the cam according to the genetic algorithm iteration step. In order to meet the kinematics and dynamics performance of the cam mechanism at the same time, the optimization problem of the cam curve is described by using the genetic algorithm, and the optimization model of the cam curve is solved.