602 results about "Visual guidance" 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 provides a dexterous hand based on multi-modal fusion control, and relates to the technical field of automatic control, the dexterous hand comprises a palm module, a palm center vision sensing module, a finger module, a fingertip force sensing module and a multi-modal control module; the palm center visual sensing module is used for acquiring visual information of the dexterous hand in a working area; the finger module comprises at least two fingers; the fingertip force sensing module is used for detecting information of contact force applied to the fingertip position; and the multi-mode control module is used for controlling the dexterous hand to grab a target object based on the visual information and the contact force information. According to the dexterous hand based on multi-mode fusion control, data of two modes of visual information and contact force information are fused, so that the dexterous hand can adapt to different grabbing environments, intelligent closed-loop control of visual guidance and force sense regulation and control is realized, and the environmental adaptability and flexibility of the dexterous hand are improved.

The invention relates to the technical field of electromyographic signal monitoring, and discloses a guided monitoring method and system based on a wireless surface electromyographic analysis feedback instrument. The method comprises the following steps: acquiring electromyographic signal time sequence data and limb movement track space coordinate information when a target muscle group moves through a multi-channel wireless surface electromyographic sensor; muscle activation intensity and fatigue change features are extracted, a joint activity angle change sequence is calculated, and a muscle-joint collaborative activity feature matrix is generated through space-time alignment fusion; analyzing signal transduction delay and amplitude matching degree in the matrix, and evaluating the nerve driving coordination level; according to the deviation from the preset standard mode, generating a real-time biological feedback signal containing an action correction instruction and a muscle activation intensity adjustment parameter; and converting into a tactile vibration mode and a visual guidance mark to be output. According to the method, synchronous acquisition and fusion analysis of multi-dimensional motion information are realized, and visual guidance is provided through multi-modal feedback.

The invention discloses a pitaya robot system based on intelligent treatment and recuperation and a control method, and the system comprises a high-precision image collection and human body image collection and three-dimensional reconstruction module which is used for precisely recognizing and positioning a treatment region and acupoints; the core physician manipulation digitization module is used for finely capturing professional treatment manipulations and standardized recuperating manipulations of deep physicians for operating pitayas through a multi-dimensional sensor array and forming a manipulation model library; the intelligent strategy generation module based on artificial intelligence can call, fuse or optimize and generate an optimal execution scheme from a corresponding model library according to a mode selected by a user; and the high-precision and compliant force control robot execution module reproduces the digitized technique of the pitaya in a high-fidelity manner under the real-time closed-loop control of visual guidance and force sense feedback. Through the double-track parallel strategy, quantification, inheritance and popularization of the high-level pitaya therapy are achieved, and application of the high-level pitaya therapy is pushed to the wide field.

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 belongs to the technical field of unmanned aerial vehicle battery replacement, and provides an unmanned aerial vehicle automatic battery replacement method and system based on 3D visual guidance, and the method comprises the steps: constructing a target feature template of each region of a battery compartment and a feed battery based on obtained standard image data; performing multi-stage pyramid matching on the obtained to-be-matched point cloud data and the constructed target feature template, and reconstructing a point cloud data set and standard image data subjected to multi-stage pyramid matching; calculating the pose deviation value of the feed battery, and combining the pose deviation value of the feed battery to obtain the actual position of the feed battery; the target position and posture information are updated according to the feed battery posture deviation value, a mechanical arm is controlled to move to the target position according to the updated posture information, and the feed battery is grabbed and placed at the designated position; and controlling the mechanical arm to grab the fully-stored battery and then return to the specified image data acquisition position, controlling the 3D camera to carry out secondary scanning, repeating the steps, and putting the fully-stored battery into the battery compartment of the unmanned aerial vehicle to complete automatic battery replacement operation.

The invention relates to the technical field of building automation and robots, and discloses a floor robot cutting system based on self-adaptive visual guidance. The technical problems that an existing floor cutting robot excessively depends on a preset path, and the adaptability is poor and the cutting precision is low when the actual working conditions that errors exist between on-site marking lines and design drawings and the ground is uneven exist are solved. An actual cutting datum line is captured and recognized in real time through a visual perception module carried on a robot body, and structured path information is generated; and then the self-adaptive control module dynamically plans and corrects the motion trail of the robot according to the deviation between the visual feedback information and the current pose of the robot so as to guide the cutting execution mechanism to accurately work, so that the accuracy loss caused by environment change and construction errors in a traditional scheme is effectively overcome, and the cutting efficiency is improved. And the operation precision, the field environment adaptability and the automation level of automatic floor cutting are remarkably improved.

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 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 discloses a vehicle body gluing method and device based on three-dimensional visual guidance, and the method comprises the steps: obtaining a to-be-glued image of a to-be-glued region of a vehicle body through a three-dimensional visual image collection device in response to the arrival of the to-be-glued vehicle body at a gluing station, carrying out the image recognition of the to-be-glued image, obtaining the first coordinate information of a positioning hole, and obtaining the first coordinate information of the positioning hole; based on the first coordinate information, second coordinate information is generated, and according to the preset positioning hole coordinate information and the second coordinate information, the first vehicle body deviation of the to-be-glued vehicle body is calculated; and performing deviation correction on the preset gluing track according to the first vehicle body deviation to obtain a target gluing track. And the gluing robot is used for gluing the to-be-glued vehicle body based on the target gluing track. According to the method, the to-be-glued image is collected through the three-dimensional visual image collecting device, the vehicle body deviation is obtained based on the actual positioning hole coordinate information and the preset positioning hole coordinate information, then the gluing track is corrected, and the accuracy of the gluing track is 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 provides a robot hospital guide method based on multi-modal data and an intelligent hospital guide robot, and relates to the technical field of robots. The intelligent hospital guide robot comprises a multi-mode sensing module, an intention understanding and decision center module and a behavior execution and guide module. The method is applied to the intelligent hospital guide robot, and comprises the following steps: collecting multi-modal data through a multi-modal sensing module; performing information fusion and intention understanding on the acquired multi-modal data through an intention understanding and decision-making center module, and generating a decision-making instruction; executing a decision instruction through a behavior execution and guidance module, so as to execute personification interaction by controlling joint movement of the intelligent hospital guide robot and / or execute visual guidance by rendering and superposing an augmented reality navigation arrow on a display screen of the intelligent hospital guide robot; the problems of unfriendly interaction, single perception, rigid planning and the like in the prior art are solved, and the triage accuracy, the user experience and the adaptability in complex medical scenes are remarkably improved.

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 relates to an intelligent ship water diversion method and system based on RTK and inertial navigation fusion, and the method comprises the steps: firstly, deploying and calibrating an RTK base station at a wharf commanding height, generating a differential correction in real time, and broadcasting the differential correction to a shipborne end; utilizing RTK surveying and mapping equipment to collect shoreline feature points, adopting a cubic spline interpolation algorithm to construct a continuous and smooth three-dimensional shoreline curve model, and fusing wharf geographic information to generate a shoreline visual map with geographic coordinates; establishing a ship coordinate system, converting inertial navigation attitude data into the coordinate system through a rotation matrix and a translation vector, fusing the inertial navigation attitude data with RTK position data, and outputting a high-precision ship pose; fusion data are transmitted through a 5G network, a shore end converts the fusion data into a local plane coordinate system and generates a real-time dynamic visual interface, the real-time dynamic visual interface is pushed to a tug terminal through an RTSP protocol, water diversion operation is assisted, high-precision perception, visual guidance and shore ship cooperation of the ship berthing process are achieved, and the water diversion safety and the intelligent level are improved.

The invention relates to the crossing field of medical rehabilitation and brain-computer interface technology, and particularly discloses a lower limb exoskeleton rehabilitation training system and method based on AR glasses and brain-computer interface control. According to the system, motor imagery electroencephalogram decoding is used as core driving force, lightweight AR visual guidance, lower limb exoskeleton mechanical assistance and functional electrical stimulation feedback are fused, and real-time information interaction among multiple modules is achieved through wireless communication; therefore, a closed-loop rehabilitation system integrating sensing, decoding, execution, multi-mode feedback and self-adaptive adjustment is constructed. Under the framework, the subjective motion intention of the patient not only can directly participate in the exoskeleton control process, but also can continuously adjust training parameters and interaction modes through dynamic monitoring of physiological signals and emotional states, so that a patient-centered lower limb rehabilitation training mode which better conforms to the neuroplastic law is achieved.

The invention relates to the technical field of robot visual guidance, and discloses a visual guidance robot material box grabbing module, which comprises a mechanical coarse positioning and state sensing unit for physically clamping a material box and collecting physical state data; a prediction type pre-positioning and dynamic reference generation unit receives the data, calls a historical deviation database, and generates a prediction target position and a temporary standard reference in parallel; the nested visual search and calibration unit moves to a prediction position and searches to obtain a complete feature image; the accurate deviation calculation and fine adjustment unit compares the image with a reference, calculates a final residual deviation and generates an accurate grabbing position; and the closed-loop learning and data feedback unit executes capturing and feeds back the final residual deviation to the historical deviation database. According to the method, a predicted target position and a dynamic temporary reference are established by using a physical state data vector and a historical deviation database, and parallel compensation of system errors and mechanical errors is realized.

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 relates to the field of data fusion, in particular to an RFID and Bluetooth fusion positioning method and system for material storage location navigation, and the method comprises the steps: obtaining the RFID tag information of a target material; according to the RFID tag information, querying a preset material storage area mapping relationship, and according to a query result, determining a target storage area where the target material is located and target shelf coordinates where the target material is located; generating a Bluetooth scanning instruction according to a determination result of the target reservoir area; broadcast signals from at least three Bluetooth beacons in the target reservoir area are received, and signal intensity parameters of the broadcast signals are analyzed; on the basis of the known position coordinates of the at least three Bluetooth beacons and the corresponding signal intensity parameters, the current accurate coordinates of the mobile terminal are calculated through a positioning algorithm; and generating and displaying a navigation path from the current position of the mobile terminal to the target shelf in real time according to the current accurate coordinate and the target shelf coordinate. And the optimal navigation path is dynamically generated and displayed on the digital map, so that intuitive visual guidance is provided for the user.

The invention belongs to the technical field of augmented reality, and particularly discloses an offline store inspection authenticity verification method based on AR environment feature point matching, and the method comprises the steps: scanning a specific region of a store through a mobile terminal, collecting environment visual feature points and pose parameters to construct and upload a sparse point cloud map, and generating a uniquely bound AR scene model; setting a virtual punch-in point in the model, and recording an anchor point coordinate under a world coordinate system of the virtual punch-in point; when the inspection is executed, the mobile terminal preloads a corresponding AR scene model based on a geographic position, extracts feature points by collecting images in real time, and matches the feature points with feature points in the model; and after successful matching, calculating a real space distance between the mobile terminal and the virtual clock-in point, and if the real space distance is smaller than a threshold value, unlocking the inspection task. According to the method, a dual verification mechanism based on pose difference and dynamic visual guidance are introduced, so that the defects of low positioning precision and easiness in counterfeiting in the prior art are overcome fundamentally, and high-precision and high-anti-counterfeiting authenticity verification of offline inspection behaviors is realized.

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.