428 results about "Visually guided" patented technology

The invention relates to a tunnel illumination control method considering visual adaptability of a driver, and belongs to the technical field of tunnel illumination control, and the method comprises the following steps: S1, employing a volume scattering point location method to obtain visual adaptability parameters of visual adaptation states of all segments in a tunnel; s2, dynamically constructing a predictive visual adaptation model of the driver group based on the visual adaptation parameters, and outputting expected visual states of the drivers according to the predictive visual adaptation model; s3, according to the expected visual state, a parameter control mechanism is adopted to control target illumination parameters of all the sections of the tunnel; s4, according to the target lighting parameters, the working state of lighting equipment in a corresponding section in the tunnel is regulated and controlled, so that the light environment in the tunnel is matched with the dynamic visual adaptability of a driver, and safe visual guidance is achieved; the method has the beneficial effects that the target illumination parameters of all the sections of the tunnel are controlled by adopting a parameter control mechanism according to the expected visual state according to the target illumination parameters.

The invention relates to a visual guidance robot automatic control method, system and device and a medium. The method comprises the following steps: firstly, acquiring a target image sequence and extracting initial visual features, and processing the initial visual features through a deep learning algorithm to output a high-resolution image; calculating a distance switching value based on the high-resolution image, and if the distance switching value exceeds a preset threshold value, performing scale distortion correction on the high-resolution image to obtain a target image; multiple frames of time sequence data are fused through a Kalman filtering algorithm, image distortion real-time compensation and feature point track stability judgment are synchronously completed, and a target positioning precision estimated value is output; and finally, according to the target positioning precision estimated value, determining the position of a grabbing point through a posture mapping rule of mapping preset grabbing feature points in a target coordinate system to a robot-based coordinate system, and based on the position of the grabbing point, optimizing and fusing track parameters through a Kalman filtering algorithm to generate adaptive track parameters. The method improves the positioning precision and track following effect of automatic control of the robot.

The invention discloses a mechanical arm autonomous grabbing system and method based on visual guidance and visual touch fusion. The mechanical arm autonomous grabbing system at least comprises a visual semantic guidance and grabbing pose generation module, a smooth grabbing control module based on visual touch fusion and a dynamic planning module based on model prediction path integration. The visual module efficiently generates a six-degree-of-freedom grabbing pose from the point cloud data by using a deep learning network; the smooth grabbing control module monitors object slippage in real time and adaptively adjusts clamping force by fusing visual and tactile information, and stable grabbing of fragile or slippery objects is achieved. And the dynamic planning module adopts a model prediction path integral algorithm MPPI to realize collision-free path planning of the mechanical arm in a complex dynamic environment. The problems that an existing mechanical arm is insufficient in sensing capacity, poor in grabbing robustness and low in path planning efficiency in an unstructured scene are solved, and the autonomous operation capacity and safety of the mechanical arm in the scenes of accompanying, intelligent sorting and the like are remarkably improved.

The invention discloses a position and posture compensation method for guiding installation of a contact network cantilever based on 3D vision and an automatic installation system. The position and posture compensation method comprises the steps that the spatial transformation relation between a 3D vision sensor coordinate system and a robot coordinate system is determined; the robot is controlled to move, and the three-dimensional point cloud data of the to-be-installed cantilever component and the three-dimensional point cloud data of the field installation foundation are collected; the collected three-dimensional point cloud data is registered with a corresponding preset CAD model, and a first real-time pose of the cantilever component in a robot coordinate system and a second real-time pose of the installation foundation in the robot coordinate system are obtained through calculation; calculating a pose compensation transformation quantity based on a pre-stored theoretical mounting pose of the cantilever, the first real-time pose and the second real-time pose; and according to the pose compensation transformation amount, planning and executing a motion track of the robot, and completing butt joint installation. The method is high in compensation precision, robustness and adaptability and high in construction efficiency, and the problem of uncertainty in automatic installation is fundamentally solved.

The invention provides an intelligent vision-guided mechanical arm precise grabbing system. The system comprises a bionic compound eye vision module for collecting multi-angle image information of a target object to generate a dynamic depth map, and a bionic touch sensing module for collecting touch information at the tail end of a mechanical arm to generate a pressure distribution heat map. And the dynamic self-optimization grabbing strategy module is used for generating a grabbing strategy by utilizing the two graphs. And the real-time trajectory planning and obstacle avoidance module optimizes a grabbing path according to the grabbing strategy, the environment obstacle information and the mechanical arm state data, and generates an optimal strategy. The robot can sense the movement of a target object and the change of environmental obstacles in real time, dynamically adjust the force and the posture in the grabbing process, and optimize the obstacle avoidance path in real time. Compared with the prior art, the system has the advantages that the aspects of dynamic obstacle avoidance, target object motion compensation, multi-modal information fusion robustness and the like are remarkably improved, the problem of insufficient adaptability in complex dynamic scenes in the prior art is solved, and high success rate and stability of a precise grabbing task under complex conditions are ensured.

The invention relates to the technical field of intelligent construction of road engineering, and discloses an expressway asphalt pavement construction data analysis and processing system, the system performs digital modeling on an asphalt mixture and anchors the asphalt mixture to a pavement three-dimensional coordinate by creating a material state vector including a static attribute, a dynamic state and a process resume, and the system adopts a heat transfer model to construct an asphalt pavement construction data analysis and processing system. And the predicted temperature of the target vector at the future interception moment of the road roller is updated in real time and forwards simulated. Meanwhile, the system calculates a dynamic compactability window according to the compaction history and the material type, compares the predicted temperature with the window, generates a feedforward control instruction of a standard, priority or waiting operation, converts the feedforward control instruction into visual guidance, and issues the visual guidance to the vehicle-mounted terminal, so that prospective control is realized. According to the invention, the conversion of construction control from passive lag to active feedforward is realized, the fineness of the compaction process is improved, and a reliable digital quality tracing mechanism is established.

The embodiment of the invention provides a pulmonary nodule automatic labeling method based on multi-modal semantic affinity iterative optimization, and belongs to the technical field of data processing, and the method specifically comprises the steps: obtaining a lung CT image and a text report; performing structured semantic analysis on the text report; performing visual feature extraction on the lung CT image; based on the key semantic information, performing semantic guidance processing on the depth visual feature representation to generate semantic enhanced visual guidance features; based on the semantic enhanced visual guidance features, calling a segmentation basic model, and generating a plurality of candidate segmentation masks by introducing an active variation mechanism; for each candidate segmentation mask, calculating a semantic matching degree score of the candidate segmentation mask; and comparing the semantic matching degree scores of all the candidate segmentation masks, and selecting the candidate segmentation mask with the highest score as a final pulmonary nodule labeling result to be output. Through the scheme of the invention, the labeling precision, adaptability and interpretability are improved.

The invention provides a robot hand-eye online calibration method based on a self-supervised consistency optimization algorithm, and the method comprises the steps: employing the posture change of a mechanical arm collected in a production task, enabling a camera to observe the posture of a workpiece and an actual error after grabbing / assembling, and building an initial hand-eye relation through combination with one-time offline calibration; the eye pose adjustment amount of the player is calculated in a segmented mode under the incremental geometric framework; the self-supervised network outputs observation reliability and an offset type from time sequence features, carries out screening and reconstruction to generate a long-term hand-eye pose adjustment amount and a single-task pose compensation amount which are respectively used for updating a hand-eye relationship and correcting a control instruction, and carries out self-supervised updating on the network based on historical records; according to the method, separation treatment of slow deviation and short-time disturbance of the structure is achieved, manual re-calibration is reduced, the positioning precision and stability of visual guidance grabbing / assembling are improved, and the method is suitable for industrial robots running on line.

The invention discloses a dynamic visual guidance method and system for cooperative assembly of multiple mechanical arms, and belongs to the technical field of industrial robot visual guidance, and the method comprises the steps: synchronously collecting an image sequence through a binocular visual system, synchronously recording the pose sequence of each mechanical arm through a robot controller, and obtaining an observation data set; obtaining a two-dimensional trajectory flow of vehicle body assembly area feature points and instrument body feature points through an optical flow tracking algorithm, and obtaining a hand-eye matrix correction through a nonlinear optimization algorithm; obtaining an updated hand-eye matrix and a local pixel compensation field through a spatial interpolation algorithm based on the re-projection error of each feature point; according to the method, self-adaptive compensation of flexible deformation of a vehicle body and dynamic reflection of an instrument is realized by adopting unsupervised clustering and spatial interpolation according to a re-projection error, and the precision of cooperative assembly of multiple mechanical arms and the self-adaptive capability of a system in a complex industrial environment are improved.

The invention discloses a ceramic workpiece grinding control system based on vision measurement, which relates to the technical field of ceramic workpiece grinding and comprises a multi-source data acquisition module, a data preprocessing module, a vision measurement and grinding calculation module and a grinding control execution module, the vision measurement and grinding calculation module comprises a vision guide contour deviation module, a grinding allowance calculation module and a grinding feeding speed adjusting module. Self-adaptive grinding is achieved through cooperation of three modules in the vision measurement module and the grinding calculation module, precise deviation is output in combination with parameters such as vision guidance and curvature, a basis is provided for allowance adjustment, allowance is optimized in combination with parameters such as adaptive material characteristics and grinding wheel abrasion, the precision and the material utilization rate are balanced, and the grinding precision is improved. The speed is dynamically adjusted according to the allowance, the temperature and the like, quality and efficiency are considered, and the machining quality, efficiency and the adaptability of the system to different working conditions are improved under multi-source data cooperation.

The invention relates to the technical field of robot automatic polishing, in particular to a vision-guided robot polishing path planning method and system, and the method comprises the steps: obtaining a workpiece surface point cloud in real time through a three-dimensional vision sensor, generating a trajectory seed point with adaptive density in combination with curvature, a normal vector and a defect semantic tag, and carrying out the positioning of a workpiece surface point; and a polishing quality evaluation function is constructed based on force sense feedback and a visual reconstruction result, so that path online correction is realized. According to the method, the polishing path and the tool posture can be dynamically adjusted, high-precision differentiation processing is achieved on the free-form surface, the edge and the defect area, and the polishing consistency and efficiency are improved.

The invention discloses an intelligent laser welding workstation for a high-voltage cable. The intelligent laser welding workstation comprises an operation table, a mechanical arm, a welding head, a camera assembly, a power assembly, a clamping assembly and a control piece. A control part is installed on the outer side of the operation table and comprises an image acquisition module, an image processing module, a track planning module, a motion control module, a quality detection module, a parameter adjustment module and a synchronous control module. Visual guidance and real-time monitoring in the welding process are achieved through the camera assembly, a welding center point is accurately positioned through an image processing algorithm, the track planning module generates a smooth welding path, and the parameter adjusting module dynamically adjusts welding parameters according to a molten pool image. The synchronous control module receives a production line signal to realize full-process automation of automatic clamping, welding and loosening; efficient and stable laser welding seamlessly integrated with the cable manufacturing process is achieved, and the automation degree, welding precision and product reliability of a production line are improved.

The invention relates to a robot intelligent control method integrating visual guidance and digital twinning technologies, and belongs to the technical field of industrial automation. The method comprises the following steps: acquiring multi-source attribute data of a robot to construct a robot control digital twin architecture, and acquiring a point cloud of a to-be-operated workpiece to position a key point location; self-adaptive noise reduction and completion are carried out on the point cloud, a to-be-operated workpiece model is constructed, features are extracted, and a feature change trend pre-judgment model is established; transmitting data by utilizing an edge computing-cloud collaborative architecture, carrying out multi-dimensional comparison in a robot control digital twin architecture, constructing a dynamic weight path planning function, solving an optimal path by adopting a genetic algorithm, and then carrying out virtual-real interaction fault simulation to optimize the path; a double-end state comparison matrix is constructed for real-time monitoring, a multi-source fusion strategy is adopted for adjustment when deviation occurs, and a linkage mechanism is triggered to suspend operation and give an alarm when the deviation exceeds a threshold value. According to the method, high-precision, self-adaptive and reliable intelligent control of the robot is realized.

The invention discloses an automatic high-precision assembly system and method based on visual feedback, belongs to the technical field of automatic assembly, and solves the problem that an existing scheme is insufficient in the aspects of automatic integration and actual usability. Comprising an embedded control unit, an XYZ Cartesian sliding table, a limiting sensor, a visual sensor, a visual mark and an upper computer processing unit, the embedded control unit is connected with the upper computer processing unit, and the embedded control unit is used for receiving a control instruction and feeding back state information. The embedded control unit is connected with a motor driver of the XYZ Cartesian sliding table and used for sending a motion control signal, and the embedded control unit is connected with the limiting sensor and used for receiving a switch signal. Working space boundary recognition and automatic calibration of the camera-robot hand-eye relation are achieved, the configuration and deployment process of a visual guidance system on the XYZ sliding table is greatly simplified, the requirement for professional skills of operators is lowered, and deployment efficiency is improved.

The invention relates to the technical field of image recognition, in particular to an intelligent solid waste recognition system based on multi-modal fusion, which comprises a data acquisition module, a visual guidance module, a recognition module and a cooperative processing module, and is characterized in that the system quickly analyzes surface information such as visible light images, three-dimensional point clouds and infrared spectrums of materials through the visual guidance module; and coding to generate a dynamic vector for guiding a subsequent refined analysis task. The identification module constructs a two-dimensional pixel map on the internal density map according to the guidance of the dynamic vectors, and utilizes a map neural network to deeply analyze local density textures so as to identify high-value components such as an internal circuit board; and the co-processing module performs template matching of the internal components and external surface anomaly detection according to the instruction so as to assess the security risk. According to the method, the external form and internal structure information of the material are deeply fused through the strategy of coarse first, fine second and dynamic guidance, and intelligent recognition of the complex electronic waste is achieved.

The invention relates to the technical field of optical three-dimensional measurement and metering, and discloses a single-camera three-dimensional coordinate measurement method and system based on full-field distance measurement, and the method comprises the following steps: S1, building a calibration field containing a control point, shooting an image of the calibration field through a monocular camera, extracting the image coordinate of the control point, carrying out the camera calibration, and obtaining a calibration field; obtaining internal parameters and external orientation parameters of the camera; and S2, controlling the laser range finder to aim at the control point in the calibration field through the non-orthogonal double-axis turntable. Submillimeter-level high-precision measurement can still be realized under the condition of a short baseline, and the problems that the precision in the depth direction is insufficient, the baseline requirement is long, parameters are easy to drift and the like in traditional stereoscopic vision measurement are effectively solved. By introducing a non-orthogonal double-shaft turntable and a visual guidance laser aiming mechanism, autonomous, rapid and accurate measurement of multiple measurement points in a large field of view is realized, and the automation degree and reliability of measurement in a complex environment are remarkably improved.

The invention discloses a visual guidance ton bag opening automatic sleeving and discharging alignment method, and belongs to the technical field of industrial automation, machine vision and intelligent packaging. According to the invention, the inner and outer ring contours of the ton bag opening, the position of the discharging pipe port and the relative offset of the ton bag opening and the discharging pipe port are identified in real time through AI vision, and the transverse, lifting and rotating multi-degree-of-freedom mechanisms are driven to cooperatively act, so that the flexible ton bag opening is sleeved into the discharging pipe in a stress-free, high-precision and one-time manner; after sleeving, it is confirmed that the bag opening completely wraps the discharging pipe through secondary visual verification, and closed-loop control of recognition, alignment, sleeving and verification is formed. The ton bag bagging machine solves the problems that traditional manual bagging is low in efficiency, inaccurate in alignment, prone to deviation, large in labor intensity and the like, achieves unmanned and high-precision automation of the whole ton bag feeding process, and is suitable for ton bag packaging production lines of powder, particles, chemical engineering, grain, building materials and the like.

The invention discloses a screw / thread bushing mounting method based on visual guidance. A visual guidance sensor and a mounting machine are mounted at the tail end of a robot at the same time; the robot moves to the pose1 to collect the point cloud I and then moves to the pose2 to collect the point cloud II; splicing the point cloud I and the point cloud II; segmenting a thread inner wall point cloud and a plane point cloud from the point cloud; fitting the central axis L1 of the cylinder by using the thread inner wall point cloud; fitting a plane by using the plane point cloud, and obtaining an intersection point coordinate P1 of the central axis L1 and the plane; respectively aligning the cylinder central axis L1 and the intersection point coordinate P1 with the standard central axis L0 and the standard intersection point coordinate P0 to obtain an offset matrix; correcting the mounting pose of the robot based on the offset matrix; according to the method, threaded hole point clouds are obtained through symmetrically-arranged collection poses; thread inner wall point cloud is obtained through point cloud segmentation, then the axial direction and the hole center position of a current workpiece threaded hole are accurately obtained, a robot is guided to smoothly complete automatic assembly, and the assembly precision is improved.

The invention discloses an intelligent substation safety measure verification and operation and maintenance management and control method and system and a storage medium, and relates to operation and maintenance automation and intelligentization of an intelligent substation. According to the invention, a cloud-edge-end collaborative architecture is constructed; edge equipment is responsible for collecting data and carrying out local intelligent preprocessing; the cloud constructs and dynamically updates a high-fidelity digital twinborn model based on the processed data, performs simulation verification on security measures, and performs real-time auxiliary verification on an edge side by using a lightweight AI model to form dual security verification; finally, the verified instruction is converted into virtual-real superposition operation guidance synchronized with the digital twinning in real time through the mobile AR terminal, and field operation is visually guided. According to the scheme, the fundamental transformation of an operation and maintenance mode from artificial experience driving to data intelligent driving is realized, the decision-making efficiency is optimized through cooperative processing, a safety defense line is constructed by utilizing dual verification, the misoperation risk is remarkably reduced by virtue of AR visual guidance, and a complete intelligent operation and maintenance closed loop is formed.

The invention discloses a mechanical arm double-shaft-hole bolt inserting method based on three-dimensional visual positioning and admittance force control, and belongs to the technical field of mechanical arm intelligent assembly.The mechanical arm double-shaft-hole bolt inserting method comprises the steps that bolt inserting position estimation is conducted through an image recognition algorithm, and a shaft hole recognition strategy combining a YOLOv8 neural network model and Hough circle detection is adopted; extracting a shaft hole normal vector by using principal component analysis, and constructing a spatial constraint to solve a tail end target attitude; formulating a two-step visual guidance strategy to avoid an observation blind area, and controlling the six-degree-of-freedom mechanical arm to move to a bolt preparation point position in stages; and finally, switching an admittance force control mode to realize fine and smooth bolt operation. According to the method, high-robustness assembly of the metal shaft hole in the unstructured environment is realized, and the problem of positioning failure caused by specular reflection interference and a depth observation blind area is effectively solved.

The invention provides a learning input degree evaluation method and system based on reaction behaviors of human-computer interaction, and relates to the technical field of input degree evaluation, and the method comprises the steps: data collection and synchronous alignment: achieving time sequence alignment through collecting physiological behavior data; feature engineering and scene adaptive modeling are carried out, and a deep learning network is constructed to extract scene sensitive features; performing multi-modal fusion and cognitive state decoding, fusing eye movement, electroencephalogram and behavior data, and outputting cognition, emotion and behavior input degree indexes; performing adaptive intervention decision and execution, and dynamically selecting content highlight or visual guidance based on reinforcement learning; personal baseline evolution and model online updating are carried out, and continuous optimization of the system is realized. The system comprises a multi-mode fusion module, a cognitive state decoding module and the like. According to the method, the cognitive response is actively stimulated through standardized interaction tasks, the problem of data splitting is solved, a multi-level evaluation system is constructed in combination with the education theory, the teaching effectiveness is improved, an evaluation intervention closed loop is formed, and the evaluation accuracy and the personalized level are improved.

The invention relates to a pure vision autonomous navigation method for a mobile robot based on ground structure line guidance. The method comprises the following steps: binocular-inertia joint perception and state estimation; carrying out ground area constraint and two-dimensional line segment extraction; performing line segment screening and geometric fitting based on motion direction constraint; carrying out three-dimensional parametric modeling and category discrimination on multiple types of ground structure lines; calculating a pose error of a relative structure line and constructing a reference trajectory; performing closed-loop motion control based on the Lapunov stability; carrying out key position judgment and motion decision making based on an image template; compared with the prior art, by introducing a visual guidance mechanism based on a ground structure line and fully utilizing natural ground structure characteristics such as a space structure boundary line, stable autonomous navigation of the mobile robot is realized without depending on artificial markers such as a high-precision map, GNSS (Global Navigation Satellite System) positioning, a two-dimensional code and a magnetic stripe; the dependence of the system on complex sensors and environment modification is effectively reduced, and the deployment and maintenance cost is remarkably reduced; meanwhile, through unified modeling of multi-type structural line features, the adaptive capacity and robustness of the navigation method in various application scenes such as warehouse logistics, park inspection, in-plant transportation and semi-structured roads are improved, high navigation stability and reliability can be kept in tasks such as fixed route inspection, lane keeping and back-and-forth running, and the navigation method is suitable for large-scale popularization and application. And the method has good engineering practical value and popularization and application prospects.

The invention relates to an iron tower welding robot system and method, the iron tower welding robot system comprises a clamping assembly, a rotating assembly for driving the clamping assembly to rotate and a welding assembly, specifically, the clamping assembly comprises at least two oppositely-arranged clamping jaws, and the distance between the clamping jaws is driven and adjusted through a clamping driving assembly; the rotating assembly comprises a rotating supporting frame, a first rotating unit is installed on the rotating supporting frame, and a second rotating unit is installed on the first rotating unit; the welding assembly comprises a mechanical arm and a welding gun, the welding gun is installed at the tail end execution end of the mechanical arm, a visual identification unit is arranged at the front end of the mechanical arm, and the relative position of the visual identification unit and the welding gun is fixed; by means of mechanical structure optimization and deep fusion of visual guidance and intelligent control, high precision, high flexibility and high automation of the welding process are achieved.

The invention relates to the technical field of man-machine interaction, and discloses a naked eye 3D interaction guiding method and system based on posture perception data, and the method comprises the steps: obtaining a continuous posture sequence of a user in a naked eye 3D display space; recognizing an action mode according to the motion vector and acceleration change of the key joint points in the continuous attitude sequence; generating a predicted interaction track according to the spatial orientation and the change trend of the action mode; comparing the predicted interaction track with a preset interaction area in real time, and taking the interaction area as a target interaction area when a main path section of the predicted interaction track is within a triggering range of the interaction area; calling interaction logic bound with the target interaction area in the naked eye 3D display space to determine a target interaction event; generating visual guidance information synchronized with the naked eye 3D display space according to the target interaction event; according to the invention, the accuracy of naked eye 3D interaction guidance can be improved.

This document describes methods and systems of adaptive fingerprint-enrollment to finger characteristics using local under-display fingerprint sensors, UDFPS, in an electronic device. The electronic device includes an adaptive-enrollment module that determines characteristics of a fingerprint based on information corresponding to a touch input detected by a touch-display device, including size and shape of an area of the touch input. Based on the fingerprint characteristics, a number and location of enrollment touches used for completing enrollment of the fingerprint are adjusted to minimize the number of enrollment touches required to complete the enrollment, minimize the amount of time needed to complete the enrollment, and maximize coverage of the fingerprint. The adaptive-enrollment module also provides visual guidance to guide the user to touch the adjusted locations of the enrollment touches and, if needed, feedback to instruct the user to adjust the location of their finger to align with the visual guidance.

The invention belongs to the technical field of image processing, and particularly relates to a glass substrate rotating jig alignment method and system based on visual guidance, and the method comprises the steps: constructing a complex gradient vector field according to the gradient of each pixel point in a glass substrate grayscale image, carrying out the four-order phase mapping of the complex gradient vector field, constructing a harmonic transformation field, and carrying out the four-order phase mapping of the harmonic transformation field; calculating a square frame saliency map according to the harmonic transformation field, calculating a circular saliency map based on a complex gradient vector field by using gradient convergence characteristics of solid dots, performing dual fusion on the square frame saliency map and the circular saliency map, constructing a target probability potential energy field, and searching extreme points in the target probability potential energy field to determine true reference point coordinates. And the rotating jig is driven to execute alignment compensation. According to the invention, the interference of metal grid textures, linear scratches and circular stains can be resisted, the rotation invariance is realized, and the high-precision visual alignment is realized.

The invention provides a method and device for relieving carsickness of vehicle passengers, electronic equipment and a medium, and relates to the field of intelligent cabins, and the method comprises the steps: obtaining the driving state data of a vehicle in response to a started vehicle carsickness relieving function; processing the driving state data through a configured animation generation algorithm to obtain a dynamic visual driving process; generating a corresponding visual guidance animation based on the dynamic visual driving process; wherein the visual guidance animation comprises a visual marker dynamically changing according to the driving state of the vehicle, and the visual marker is used for guiding the visual perception of the passenger to be consistent with the vestibular perception. According to the method, the driving state data is collected based on the original hardware of the vehicle, the dynamic visual driving process is constructed through the animation generation algorithm, the visual guidance animation is generated, the visual marker dynamically changes along with the driving state of the vehicle, visual perception of passengers can be accurately guided to be consistent with vestibular perception, and carsickness reaction is effectively relieved.

The present application relates to the technical field of automatic production equipment, in particular to a multi-layer trolley side-pushing type feeding and discharging system based on visual guidance and a control method thereof, comprising a trolley base and a supporting system, a multi-layer silo storage unit, a side-pushing type cylinder execution mechanism, a visual guidance detection device, a trolley guiding and positioning assembly, a protection and safety assembly, and an electric control system. The present application solves the technical problems of low feeding precision, poor orderliness, unstable trolley docking, insufficient protection, and complicated operation and maintenance of the existing multi-layer trolley feeding and discharging system, realizes high-precision and orderly side-pushing feeding and discharging of multi-layer materials, has high stability of trolley docking, high integration and modularity of the overall structure, and is convenient to operate and maintain, safe and perfect in protection, and can be widely applied to the side-pushing type feeding and discharging process of multi-layer materials in the automatic production lines of automobile parts, 3C electronic products, precision hardware, etc., greatly improving the feeding and discharging rhythm and production efficiency of the production line.

The invention provides a visual element automatic typesetting optimization method and system for commercial advertisement design, and relates to the technical field of advertisement design, and the method comprises the steps: building a cognitive preference model through obtaining user behavior characteristics, carrying out visual element semantic association analysis to form a dependency graph, and calculating layout tension field distribution. And generating a multi-level visual guidance path to realize adaptive typesetting, and performing iterative optimization based on user feedback data. According to the method, personalized accurate layout of the advertisement visual elements can be realized, the user visual experience and the advertisement conversion efficiency are improved, and the design cost is reduced.

The invention relates to the technical field of man-machine interaction, and discloses a special group-oriented visual guidance type interactive interface customization design method, which comprises the following operation steps of S1, multi-modal perception data acquisition: acquiring multi-dimensional physiological and behavior data of a user through gamification tasks (such as finding different, memory cards and color matching); s2, constructing a dynamic user capability model, and integrating perception data and an interaction behavior baseline (such as a task completion path, time consumption and an error rate); according to the visual guidance type interactive interface customization design method oriented to the special group, through multi-mode perception data collection (such as physiological and behavior data collection through a gamification task) and dynamic user ability model construction, 'obstacle type-use scene-ability short board 'of the special group is accurately described, a digital user ability file is formed, and the user ability file is displayed in a user interface. The problems of fuzzy user portraits and insufficient pertinence in existing design are solved, and interface customization has clear data support.