509 results about "Posture correction" patented technology

The invention provides a teaching-free welding robot path planning system based on visual autonomous learning, and relates to the technical field of industrial welding, and the teaching-free welding robot path planning system comprises a pose compensation module which is used for arranging three infrared reflective mark points on the surface of a clamp base in an L shape, collecting original point clouds of the mark points and a workpiece by using a stereo camera, and preprocessing the point clouds; generating a pose compensation matrix based on the offset of the actual coordinate and the theoretical coordinate of the mark point, and outputting a de-noising point cloud data set and a compensation matrix; and the pose correction module is used for fitting a workpiece plane equation by adopting a random sampling consistency algorithm on the basis of the de-noised point cloud data set, acting a pose compensation matrix on the workpiece plane equation, correcting a pose error caused by clamp drifting, calculating a welding seam track end point coordinate and outputting a corrected welding seam pose parameter and a scanning pose instruction. According to the method, clamp drift can be compensated, weld joint poses can be corrected, three-dimensional features are extracted, a collision-free path is planned, and the welding precision, efficiency and automation degree are improved.

The invention relates to the technical field of high-speed railway operation and maintenance, and provides a 4C detection-based high-speed railway overhead line system completion acceptance method and system, and the method comprises the steps: collecting overhead line system image data, obtaining pose data and spatial positioning data of an inspection vehicle, carrying out the synchronous calibration processing, building a mapping relation, and obtaining a calibrated overhead line system image; inputting the calibrated overhead line system image into a multi-scale target detection model, outputting a detection result, performing pose correction on the detection result, and generating a three-dimensional positioning coordinate in combination with the mapping relation; constructing a time sequence feature vector, inputting the time sequence feature vector into the prediction model, outputting a defect evolution trend and a risk probability of the part, and grading the risk probability; and according to the risk level and the spatial positioning data, combining a knowledge graph driven rule engine, generating an intelligent work order, mapping the intelligent work order to field equipment, and collecting and feeding back a maintenance result. According to the method, the recognition and spatial positioning precision of the parts of the overhead line system is improved, and the safety and reliability of completion acceptance of the overhead line system of the high-speed rail are improved.

The invention provides a physical training posture correction method based on machine vision, which comprises the following steps: acquiring an athlete training image sequence through a multi-view image acquisition system and preprocessing the athlete training image sequence, extracting three-dimensional posture key points of a human body by utilizing a depth posture recognition model, constructing a skeleton model and calculating real-time kinematics characteristic parameters, and performing multi-dimensional comparison with standard parameters to generate a posture deviation evaluation report, thereby generating a personalized multi-modal correction feedback scheme, and establishing a personal athlete movement feature database to realize adaptive standard parameter optimization. According to the method, the training postures of athletes can be accurately recognized and corrected in real time, the training effect can be improved, sports injuries can be prevented, and training individuation and scientificity are improved.

The invention discloses a horizontal five-axis turning and milling composite center with a self-adaptive matching system. The horizontal five-axis turning and milling composite center comprises a tool turret, a boring tool mechanism, a tool changing area and a control system. A radio frequency identification reading device is arranged in a tool changing area of the tool turret and the boring tool mechanism, and an RFID chip tag is attached to the outer surface of each tool and used for storing tool serial numbers, specifications and length compensation parameters. And the control system realizes self-adaptive matching and sequential error correction of the cutter and the working procedure through radio frequency identification. The tool changing area is provided with a visual monitoring assembly which comprises a plurality of sets of industrial cameras, an adjustable light source and a structured light stripe illumination module and is used for detecting the clamping posture, the abrasion state and the type of a tool. The system has self-learning and digital twinning simulation functions, and can simulate the motion trail of the cutter and predict the interference risk before the cutter is changed. According to the method, integrated control over automatic tool recognition, posture correction, abrasion detection and path prediction is achieved, and the tool changing precision, the operation stability and the automation level of the horizontal five-axis turning and milling composite center are remarkably improved.

The invention discloses a safety rope hook suspension state detection method and system for high-altitude operation, and relates to the technical field of image recognition, and the method comprises the steps: determining a stability region candidate set based on the distribution density and time interval change condition of an image center point in each grid region, a target suspension area is screened out according to the stability area candidate set; acquiring a current hook image after the target suspension area is acquired, extracting edge contour features of the hook based on the hook image, and calculating current spatial attitude parameters of the hook; comparing the current space attitude parameter with a preset hook standard attitude interval, and judging whether the previous space attitude parameter belongs to the hook standard attitude interval or not; when the current space attitude parameter does not belong to the standard attitude interval of the hook, calculating an attitude adjustment vector; real-time accurate detection and active posture correction of the hanging state of the safety rope hook are achieved, and the safety of high-altitude operation personnel is effectively guaranteed.

The invention relates to the technical field of automatic control, in particular to a detection equipment attitude real-time correction system which comprises an attitude trajectory extraction module, a trajectory stability evaluation module, an interference area recognition module, a light spot trajectory reconstruction module and an attitude correction control module. According to the invention, through comprehensive extraction of the direction change trend, the angle difference and the trajectory overlapping condition in the light spot image sequence, the trajectory trend of the attitude change between continuous frames is established, so that the identification of the attitude offset evolution process is more detailed, the attitude change stability analysis is realized in the time sequence dimension, and the accuracy of the attitude change is improved. Interference area identification is carried out by means of luminance continuity and spatial distribution consistency of light-emitting pixels, real light spots and lagging residual signals can be effectively distinguished, a light spot track path is reconstructed on the basis of interference removal, and real-time calculation of a track dynamic offset direction and an angle change amplitude is combined with track correction rule setting, so that the accuracy of track correction is improved. And the specific correction action matching of the deviation state is realized.

The invention belongs to the technical field of welding automation, and provides a welding gun posture self-adaptive adjusting method and system for a complex welding seam, and the technical scheme is that point cloud data of a to-be-welded welding seam is converted into a welding seam track, key features of the welding seam are extracted based on the welding seam track, and key points of the welding seam are determined; calculating the tangential direction and the normal direction of each welding seam key point; aiming at different types of welding seams, performing segmented path planning in combination with the key characteristics of the welding seams to obtain an ideal movement track of a welding gun, and determining the posture of the welding gun based on the ideal movement track of the welding gun in combination with the tangential direction and the normal direction of each welding seam key point; calculating the deviation between the welding gun and the welding seam according to the point cloud data collected in real time and the ideal track of the welding seam, generating a posture correction instruction according to a deviation calculation result, and adjusting the path and posture of the welding gun to ensure that the welding gun always keeps an optimal angle with the surface of the welding seam. And the welding quality and adaptability are improved.

The invention provides a muscular-bone rehabilitation posture correction method and system based on visual identification, and the method comprises the steps: firstly collecting the posture video data of the muscular-bone rehabilitation training of a rehabilitation object, and covering the joint movement, muscle contour change and body balance state change processes; analyzing the posture video data to generate joint movement tracks, muscle force application association and body balance state features, corresponding the joint movement tracks, the muscle force application association and the body balance state features to a preset muscle-bone rehabilitation stage target to establish a multi-dimensional adaptation relationship, and generating layered and staged correction guide information according to the multi-dimensional adaptation relationship, joint, muscle and balance adjustment layers are divided according to priorities, a specific adjustment mode is provided, new posture video data after adjustment is obtained, repeated operation is conducted, correction guide information is updated according to deviation changes, accurate and dynamic muscle-bone rehabilitation posture correction is achieved, and the rehabilitation effect and efficiency are improved.

The invention discloses a piano playing posture dynamic correction method and system based on multi-dimensional data, and relates to the technical field of posture correction, and the method comprises the steps: collecting the multi-dimensional data of a player in real time through vision, pressure and electromyographic signal sensors, and generating an original data set; performing cleaning, noise reduction and feature extraction on the original data set, generating a preprocessed data set, and extracting biomechanical feature parameters; based on the extracted biomechanical characteristic parameters, a biomechanical model reflecting the posture state and the potential deviation of the player is constructed, and through multi-dimensional data acquisition and fusion, deep learning model analysis and a closed-loop optimization system, the posture state and the potential deviation of the player can be analyzed. The problems that an existing piano playing posture correction method cannot dynamically monitor in real time, accurately recognize posture deviation, provide personalized correction suggestions and continuously optimize the correction effect are solved.

The present invention provides a teaching-free welding robot path planning system based on visual autonomous learning, which relates to the field of industrial welding technology. The system comprises: a posture compensation module for arranging three infrared reflective marking points in an L-shape on the surface of a fixture base, using a stereo camera to collect the original point cloud of the marking points and the workpiece, and preprocessing the point cloud; generating a posture compensation matrix based on the offset between the actual coordinates and the theoretical coordinates of the marking points, and outputting a denoised point cloud data set and the compensation matrix; a posture correction module for fitting the workpiece plane equation based on the denoised point cloud data set using a random sampling consistency algorithm, applying the posture compensation matrix to the workpiece plane equation, correcting the posture error caused by fixture drift, calculating the coordinates of the weld trajectory endpoints, and outputting the corrected weld posture parameters and scanning posture instructions. The present invention can compensate for fixture drift, correct weld posture, extract three-dimensional features, and plan a collision-free path, thereby improving welding accuracy, efficiency, and automation.

The invention discloses an aviation transient electromagnetic pod coil attitude correction method and system, and belongs to the field of aviation geophysical exploration, and the system comprises a surface scanning industrial camera module which is used for obtaining the image information of a suspension coil in real time; the industrial-grade integrated navigation module is used for outputting inertial navigation data; the time synchronization and data acquisition module is used for establishing a time unification mechanism; the visual processing module is used for extracting the image processed by the time unification mechanism to obtain visual features; the inertial navigation resolving module is used for obtaining an inertial navigation state of a coil attitude angle through angular velocity integration; the data fusion and attitude estimation module is used for performing fusion calculation by combining the visual features and the inertial navigation state to obtain a fusion result; and the projection area and magnetic moment calculation module is used for calculating the ground projection area and the effective emission magnetic moment component of the coil according to the fusion result. According to the method, the system complexity and the electromagnetic interference risk caused by multi-inertial navigation layout are reduced, and the detection precision and stability of the aviation transient electromagnetic data are improved.

The present application relates to the technical field of image processing, and particularly relates to a two-stage tool surface defect detection method and system, which comprises the following steps: performing grayscale, posture correction, cutting and labeling operations on a tool surface channel image to be detected to obtain a corrected grayscale image corresponding to each sub-image and a number of the tool surface to be detected; inputting each sub-image into a trained residual network and a support vector machine respectively to output a first predicted defect probability value and a second predicted defect probability value of each sub-image and obtain a fusion defect probability value of each sub-image; regarding a sub-image with a fusion defect probability value greater than or equal to a threshold value as an abnormal sub-image; based on each abnormal sub-image and a normal sub-image with the same number, forming a defect pair of each abnormal sub-image; inputting the defect pairs of all abnormal sub-images into a trained twin transformation detection network to output defect region features and segmentation results in each abnormal sub-image. The present application improves the accuracy, reliability and efficiency of tool surface defect detection.

The invention belongs to the technical field of three-dimensional reconstruction, and particularly discloses a three-dimensional human body and scene interaction reconstruction method and system. The method is a three-dimensional human body and scene interactive reconstruction method for monocular video input, not only can quickly complete three-dimensional Gaussian reconstruction of a human body, a static scene and a moving object, but also can quickly complete the three-dimensional Gaussian reconstruction of the human body, the static scene and the moving object by introducing technical means such as posture correction, camera external parameter space regularization, joint reconstruction consistency loss and layered fusion rendering. And accurate alignment of the human body, the scene and the object in spatial positions, shielding relations and illumination styles is ensured, and dynamic interaction reconstruction conforming to real physical logic is realized. Finally, a joint rendering image with high fidelity, continuous time sequence and consistent structure can be generated, a stable and reliable three-dimensional expression capability is provided for complex human body actions, object interaction and scene understanding, and the three-dimensional interaction reconstruction quality and application value under the monocular video condition are greatly improved.

The invention relates to the technical field of tunnel safety monitoring, in particular to a strong noise tunnel point cloud monitoring method based on improved RANSAC and dynamic residual, which comprises the following steps: firstly, collecting two-dimensional point cloud data of a cross section of a tunnel, and performing attitude correction through ground baseline fitting to unify a coordinate system; afterwards, de-noising is carried out by adopting a vault-dominated improved RANSAC algorithm, and the algorithm effectively filters out strong noise and retains key lining points through constraint sampling, model geometric constraint and dynamically adjusted residual error threshold values; and performing nonlinear least square complete circle fitting on the denoised point cloud, and accurately extracting circle center and radius parameters. And finally, based on the absolute deviation, the relative deviation, the abrupt change increment and other multi-dimensional indexes of the radius, safety evaluation and early warning are carried out in combination with a standard threshold system. According to the invention, the robustness and precision of tunnel contour monitoring under complex working conditions of strong noise, equipment installation deviation and the like are obviously improved.

The invention discloses a GIS in-place robot coordination control method with a posture correction function, and belongs to the technical field of robot coordination control. The method comprises the following steps: establishing a 2D-3D coordinate mapping corresponding relation; fusing the corresponding relation with an operation state predicted by an IMU-based inertial measurement and system dynamics model; performing error calculation on the obtained 6D pose information and target pose information; constructing a nonlinear kinetic equation of the robot, and converting a control target into an optimization problem of various constraints; and converting the obtained control instruction into a torque signal for actually driving the robot to move. According to the method, the influence of mismatching on pose estimation is effectively inhibited by establishing the 2D-3D coordinate mapping relation; through a joint torque PID control algorithm, the torque required by each joint is calculated in real time, and high-precision tracking of an expected trajectory is realized; an MPC optimization control framework with multiple constraints is constructed, and precise, smooth and safe coordination control over the GIS in-place process is achieved.

The invention relates to a method for visually correcting a running posture and a running machine thereof, and relates to the technical field of fitness equipment, and the method comprises the following steps: step 100, collecting a starting signal of the running machine; step 101, acquiring a running posture image of a user; step 102, identifying foot feature points from the running posture image; step 103, determining a grounding part based on the foot feature points; step 104, when the grounding part is consistent with a preset reference part, determining an overturning angle based on the foot feature points; and step 105, if the overturning angle exceeds a preset overturning interval, generating and displaying a running posture correction suggestion according to the running posture image and a preset reference part. The running posture correction method and device have the advantages that the pertinence of running posture correction is improved, and the running posture of the user can be accurately recognized.

The invention relates to the technical field of laser radar positioning, and particularly discloses a robot positioning method, system, equipment and medium based on laser SLAM. 3D feature point clouds from a laser radar are collected, IMU data are synchronously received, preliminary posture correction is conducted on feature points through posture pre-transformation, the corrected 3D point clouds are projected to a two-dimensional plane, and the 3D point clouds are projected to the two-dimensional plane; forming projection feature points containing height information, and extracting the projection feature points as two-dimensional feature point cloud for registration; matching the two-dimensional feature points of the current frame with a historical sub-map by adopting an RANSAC point cloud registration algorithm, and updating the sub-map according to a registration result; according to the method, the initial speedometer output is filtered based on Kalman filtering to obtain the final speedometer output, the estimation precision is improved, a smooth and high-precision speedometer result is output, support is provided for accurate positioning and navigation of a robot in a complex environment, and the robust SLAM mapping capability in a dynamic, sparse or strenuous motion environment is achieved.

The invention relates to a wearable fitness monitoring system that uses advanced sensor technology to track real-time muscle engagement, posture, and fatigue levels during physical activity. The system comprises a capacitive sensor system, incorporating elastic silver fiber cloth and medical-grade silicone, for precise muscle movement detection; a motion sensor for tracking movement along multiple axes; and an AI-powered processing unit to provide ergonomic feedback, prevent injuries, and optimize performance. It features dynamic self-calibrating sensors that adjust to user-specific movements using machine learning algorithms. The system offers personalized workout plans, adjusting in real-time based on biometric feedback, environmental conditions, and muscle fatigue. Additionally, it integrates Bluetooth Low Energy (BLE) for wireless communication, haptic feedback for posture correction, and AR / VR for immersive workout guidance. The system includes cloud-based data storage with encryption and supports blockchain for secure data management, offering a comprehensive, personalized fitness experience that improves workout efficiency and safety.

The invention relates to the field of three-dimensional reconstruction, and provides a pig weight estimation method, device and equipment, a medium and a computer program product, and the method comprises the steps: obtaining multi-view image data of a to-be-detected pig; generating sparse point cloud data based on the multi-view image data; generating a multi-view rendering image based on the sparse point cloud data and the three-dimensional Gaussian data; the three-dimensional Gaussian data is obtained by converting the sparse point cloud data; and inputting the three-dimensional Gaussian data into a weight estimation model to obtain pig feature information, and estimating the weight of the to-be-detected pig based on the pig feature information. According to the method, the accuracy of non-contact weight estimation of the pigs is improved and the implementation cost is reduced through an individual weighing posture correction, weighing scene three-dimensional reconstruction and posture semantic fusion associated weight estimation method.

The invention discloses a health monitoring and correction method and device based on posture recognition, a medium and a product, and relates to the field of computer vision and health management cross technologies, and the method comprises the steps: obtaining RGB image data, depth map data and radar observation data in real time; respectively carrying out normalization processing on the RGB image data and the depth map data; the RGB image data after normalization processing and the depth map data after normalization processing are fused into RGB-D image data; an HRNet-Spine model is constructed, and the HRNet-Spine The RGB-D image data and the radar observation data are input into an HRNet-Spine model, and a spine key point detection result is obtained; obtaining a health score of the current posture based on a spine key point detection result; a gesture correction suggestion is generated based on the health score for the current gesture. According to the invention, efficient and accurate personnel health monitoring and real-time posture correction can be realized.

The invention relates to the technical field of tunnel monitoring, in particular to a construction tunnel laser scanning point cloud attitude correction method based on multi-feature fusion, and the method comprises the steps: S1, synchronously extracting a ground baseline feature, a haunch symmetry axis feature and a vault circle center feature from a tunnel section laser scanning point cloud; s2, constructing confidence quantitative models for the three types of features respectively; s3, calculating the weight of each feature through a normalized exponential function based on the confidence of the three types of geometric features obtained in the step S2; setting a confidence threshold value, and forcibly returning to zero weight to shield failure features when the confidence threshold value is lower than the threshold value; when all the weights return to zero, activating a degradation protection mechanism to give equal weights; and finally, weighting and fusing the horizontal rotation angles of the three types of features according to weights, and outputting a correction angle. According to the method, the problem of systematic deviation caused by interference of a single reference is solved, and the correction precision and robustness in a complex construction environment are remarkably improved.

The invention relates to the technical field of pipeline deformation monitoring, and discloses a buried steel pipe deformation degree detection method and system based on multi-sensor fusion. The method comprises the steps that data of an accelerometer and a magnetometer are collected and processed to obtain an initial space orientation angle estimated value, the initial space orientation angle estimated value is compared with a preset steel pipe axis model, and if deviation exceeds a threshold value, dynamic deviation compensation is conducted through gyroscope data to obtain a real-time posture correction vector; extracting a multi-point detection sequence fitting deformation curve to obtain a continuity parameter set, and screening a low-consistency paragraph fusion neural network to obtain a multi-point deformation data set; and determining a final deformation evaluation value through underground interference simulation, noise modeling and particle adjustment, matching the final deformation evaluation value with historical records, and generating an alarm and risk early warning report when the matching degree is low. The method can improve the detection precision and data consistency, and guarantees the safe operation of the buried steel pipe.

The invention discloses a construction method and system of a three-layer inclined quadrangular pyramid grid structure, and relates to the technical field of building steel structure construction. The method comprises the steps of building an intelligent monitoring control system, carrying out BIM collaborative assembly and calibration, carrying out multi-dimensional graded lifting, carrying out adaptive attitude correction, carrying out BIM collaborative in-place recording and the like. The corresponding system comprises an intelligent monitoring control module, a BIM collaborative management module, a hydraulic synchronous lifting execution module, a posture correction module and an unloading in-place module. Through deep integration of a distributed control network and a BIM technology, dynamic monitoring, self-adaptive adjustment and visual management of the construction process can be realized, the accuracy, safety and efficiency of construction of the three-layer inclined quadrangular pyramid grid structure are improved, and the method is suitable for large-span steel structure grid installation engineering.

The utility model discloses a badminton racket for swing correction, which belongs to the technical field of sports auxiliary appliances and comprises a racket rod component, an auxiliary racket surface movably mounted at the upper end of the racket rod component and a front racket surface rotatably mounted on the auxiliary racket surface, and symmetrical return springs are connected between the auxiliary racket surface and the front racket surface. The racket rod assembly comprises a rod body, a grip rotatably installed at the lower end of the rod body and a handheld groove formed in the grip, the auxiliary racket face is movably installed at the upper end of the rod body, the handheld groove can be used for correcting and training the racket holding posture of a player, and the racket can be adjusted by adjusting the racket face and the grip, so that the racket can be used for correcting and training the racket holding posture. The device is suitable for correcting the racket holding posture of the left hand or the right hand, so that the applicability of the device is improved; the rotatable front racket surface is matched with the auxiliary racket surface, so that the device can be used for correcting the racket swinging strength and the racket swinging action of a training player, and the training efficiency of the player is improved.

The invention discloses a shoulder joint rehabilitation action image recognition and real-time posture correction feedback method and system, and belongs to the technical field of medical image processing and computer vision, and the method comprises the steps: collecting a rehabilitation training image frame sequence through an RGB camera; inputting the image into a human body analysis model, extracting skeleton key point coordinates and calculating a joint angle sequence; constructing the skeleton key points into a space-time diagram structure, and inputting the space-time diagram structure into a space-time diagram convolutional network for action classification and recognition; aligning and comparing the actual joint angle with the standard action template by adopting a dynamic time warping algorithm to calculate a deviation vector and an action compliance score; a standard posture skeleton line and an angle deviation indicating arrow are overlaid and rendered on an image, the compliance degree of each joint is displayed in a color gradient mode, an action compliance degree score and personalized correction suggestions are output, the error posture recognition accuracy is larger than 92%, the feedback delay is smaller than 100 ms, and the technical problem that home rehabilitation lacks professional action guidance is solved.

The invention relates to the technical field of foot health and motion monitoring, in particular to a multi-motion-scene-oriented foot motion data acquisition and intelligent analysis guidance method, which comprises the following steps of: acquiring foot three-dimensional static form and plantar pressure data through a foot correction shaping box, and establishing a foot geometric model with an anatomical mark; then, a nine-axis inertial measurement unit and a pressure sensor at a shoelace knob in the shoe are used for collecting time sequence foot motion data of multiple motion scenes; extracting multi-modal features after fusion, inputting the multi-modal features into a pre-training multi-task model, and outputting exercise habit classification, technical action scoring and injury risk assessment; finally, a sports biomechanics knowledge base is adjusted, and personalized suggestions of posture correction, muscle strength training and equipment adjustment are generated. The method is suitable for various exercise scenes, accurate in data acquisition, comprehensive in analysis dimension and high in guidance suggestion pertinence, the exercise normalization of the user can be effectively improved, and the exercise injury risk can be reduced.

The invention relates to the technical field of image processing, in particular to an identity recognition method and system based on image processing. When identity recognition is carried out, image illumination compensation operation is carried out on a collected image through a closed-loop process of semantic perception, type classification and mode-based compensation fusion, the type classification is divided into a low-light scene and an overexposure scene, and for the low-light scene, the overexposure scene is divided into an overexposure scene and an overexposure scene; for an overexposure scene, performing image enhancement processing on the pre-screened face image by adopting a face region distribution guided Retinex algorithm, and for the overexposure scene, pertinently adjusting cliplimit parameters of a CLAHE algorithm by sensing gradient features of a highlight region and a key texture region to realize image enhancement processing on the pre-screened face image; according to the invention, the method achieves the precise adaptation of the face structure, retains the illumination restoration of key details, solves the global defects of an existing method, and lays a high-quality image foundation for the subsequent shielding restoration and posture correction.

The invention relates to a geographic information surveying and mapping method and device based on a laser radar, equipment and a medium. The method comprises the following steps: according to hardware parameters of sensors such as a laser radar and a multispectral camera, carrying out space-time calibration processing on the sensors deployed on a mobile platform to obtain space-time synchronous multi-source data; through semantic segmentation and three-dimensional association processing, dynamic semantic reference points are extracted, and a dynamic semantic reference point space-time constraint database is constructed; according to the dynamic semantic reference point, IMU measurement data and wheel speedometer speed data, pose resolving processing is carried out through an adaptive filtering algorithm; and performing hierarchical modeling according to the platform pose and the original point cloud, and fusing satellite geographic data to output a multi-scale geographic information result. According to the method, through the technical means of multi-source data space-time collaborative collection, dynamic semantic datum point extraction, self-adaptive pose correction and the like, the precision and efficiency of geographic information surveying and mapping are remarkably improved, and the adaptability to the dynamic complex environment in the drawing process is enhanced.

The invention provides an astronaut physical exercise process intelligent guide feedback method and system, and relates to the technical field of data feedback, and the method comprises the steps: obtaining three-dimensional motion track data in an astronaut training process, and carrying out kinematics analysis calculation to obtain a joint angle sequence and limb space posture parameters; the method comprises the following steps: obtaining a deviation vector by comparing and analyzing with a standard action template, generating a posture correction instruction and feeding back in real time, and regulating and controlling load parameters of training equipment, thereby realizing accurate guidance and intelligent correction in the astronaut training process, and improving the training effect and safety.

The invention discloses a motion posture correction system and method based on AI drive, and belongs to the technical field of artificial intelligence and motion health, and the motion posture correction system comprises a multi-mode perception layer, an intelligent preprocessing layer, an AI decision layer, a multi-dimensional feedback layer and a user platform; the multi-modal sensing layer fuses vision, biosensing and environmental data; the intelligent preprocessing layer improves the data quality through a cross-modal calibration and enhancement technology; the AI decision-making layer combines transfer learning and biomechanical analysis to realize personalized judgment; the multi-dimensional feedback layer provides graded intervention and risk early warning; the user platform supports data management and model evolution. According to the AI driving-based motion posture correction system and method, scientific and efficient motion posture correction is realized through multi-modal perception, personalized decision and accurate feedback.