928results about "Image feed-back" patented technology

The invention relates to the technical field of chip mounting processing, and discloses an optical alignment system and method for chip mounting processing, and the method comprises the steps: collecting a target chip image and a target substrate image in a mounting process through an upper visual field camera disposed above a suction nozzle assembly and a lower visual field camera disposed above a substrate carrying platform; chip edge accurate coordinates in the target chip image are extracted, and reference mark accurate coordinates in the target substrate image are extracted; solving a chip mounting process compensation parameter matrix of an upper and lower camera-suction nozzle-substrate four-coordinate system in the chip mounting process based on the chip edge accurate coordinate and the reference mark accurate coordinate; calculating an X-Y-theta three-dimensional alignment compensation vector in the chip mounting process according to the mounting process compensation parameter matrix; on the basis of the X-Y-theta three-dimensional alignment compensation vector, the optimal mounting track parameter is calculated, an execution instruction sequence is generated, the problem of error accumulation caused by traditional independent calibration is effectively solved, and the alignment precision is remarkably improved.

The invention relates to the technical field of digital twinning control, and discloses a composite structure prefabricated segment digital twinning-adaptive assembly correction method and system, and the method comprises the steps: reading BIM geometric model data, and constructing an assembly reference coordinate system and a digital twinning geometry of a prefabricated segment; composite data are collected in real time, and end tooth groove boundary feature point cloud is extracted; matching the actually measured point cloud with the digital twinborn geometry through a dynamic point cloud registration technology, calculating a six-degree-of-freedom pose error vector, and generating a predicted total pose error vector in combination with a pre-constructed pose drift prediction model; based on the error vector, a mechanical fine adjustment jack is driven to execute position and posture adjustment until the position and posture are converged, and then tooth groove precise meshing and mechanical locking are completed; according to the method, through the synergistic effect of the dynamic mapping of the digital twinborn model and the self-adaptive correction algorithm, high-precision dynamic correction of the multi-combination structure segment assembly process is achieved on the premise that an original mechanical connection structure is not changed.

The invention relates to the technical field of automatic workpiece grabbing and visual servo control, and discloses a workpiece grabbing method and system based on visual feedback, and the method comprises the steps: obtaining a real-time image through a front-view camera, a side-view camera and a top-view camera, and extracting surface features through a feature fusion network; inputting the features into a pose estimation model based on a particle filtering framework, and iteratively updating the pose in combination with a multi-dimensional observation likelihood function to generate prediction parameters; constructing a multi-target path planning model based on the parameters, and optimizing the path by adopting a dynamic planning algorithm with the shortest path and the minimum joint movement as targets; a hierarchical control model is established, a strategy layer performs global planning, an adjustment layer corrects a local path, and an execution layer realizes trajectory tracking through visual servo control and outputs a control instruction to complete grabbing. Through multi-view perception, robust pose estimation, global optimization path planning and hierarchical control, the precision, efficiency and stability of workpiece grabbing in a complex environment are improved.

The invention belongs to the technical field of laser processing, and particularly relates to a special-shaped curved glass laser cutting track planning method. According to the method, the instantaneous thermal effect and the historical thermal accumulation effect are subjected to coupling calculation, high-precision prediction and compensation of thermal deformation in the laser cutting process are achieved, the accuracy of the cutting track is improved, contour deviation caused by thermal deformation is avoided, and the geometric precision is improved; according to the local geometric complexity of the special-shaped curved glass, regions are divided, and differential virtual scanning layers and scanning modes are matched, so that the dynamic balance of efficiency and precision is guaranteed, the processing quality of regions with high curvature, thin walls and the like is guaranteed, the cutting speed of flat regions is increased, and the processing period is shortened; by monitoring the temperature and feeding back actual thermal historical parameters during cutting, model parameters are reversely optimized by using contour precision data after cutting is completed, so that robustness and stability are enhanced, and the yield and process reliability of laser cutting of the special-shaped curved glass are improved.

The invention provides an industrial robot automatic welding method and control equipment, and relates to the technical field of machine control. The method comprises the following steps: acquiring three-dimensional point cloud data of a workpiece, and adjusting a pre-constructed BIM model of the workpiece according to the three-dimensional point cloud data, so that the adjusted BIM model is aligned with an actual workpiece position; obtaining a theoretical welding seam path from the adjusted BIM model; acquiring an actual welding seam image of the workpiece; according to the actual welding seam image and the theoretical welding seam path, calibration parameters of the robot are determined, and a final welding path is determined according to the calibration parameters; and according to the final welding path and the material and thickness of the workpiece, a final control instruction set is determined, and the robot is controlled to conduct automatic welding according to the final control instruction set. The welding precision can be improved, meanwhile, manual intervention is not needed, the welding efficiency can be greatly improved, and the method can adapt to complex and changeable welding scenes.

The invention provides a control method and system for a surface shape of an optical device, and the method comprises the steps: carrying out the initial grinding and polishing of the optical device, carrying out the real-time detection through a multi-frequency-band stress detector, obtaining the stress distribution and surface wave front data, and obtaining an initial detection result; a phase shift interferometer and a composite laser confocal probe are used to carry out depth surface shape measurement based on the initial detection result, and adaptive finishing is carried out on an abnormal area to obtain a surface shape finishing log; according to the initial detection result and the finishing log, executing step-by-step load irradiation and stress tracking, and collecting surface shape change under photo-thermal coupling to obtain surface shape evolution information; and according to the surface shape evolution information, performing partition dynamic compensation and real-time detection until a surface shape control result meeting requirements is obtained. According to the method, secondary deformation caused by internal stress release is recognized and corrected through combination of multi-frequency-band stress detection and high-precision interference measurement, high-precision control over the surface shape of the optical device is achieved, and the method is suitable for scenes with high requirements for the surface shape of the optical element.

The invention relates to the technical field of pressure control, in particular to a dynamic pressure control system and method of a strapping machine. The method comprises the following steps: acquiring information data of an object to be bundled; performing three-dimensional modeling on the to-be-bundled object information data to generate three-dimensional modeling data of the to-be-bundled object; binding mode confirmation is conducted on the binding machine according to the three-dimensional modeling data of the to-be-bound object, binding mode data are obtained, and the binding mode data comprise a single-layer binding mode and a multi-layer binding mode; initial strapping pressure setting is carried out on the information data of the to-be-strapped object based on the single-layer strapping mode, and single-layer strapping initial pressure data is obtained; and carrying out object deformation binding pressure adjustment on the single-layer binding initial pressure data to generate single-layer binding pressure adjustment data. Through three-dimensional modeling, dynamic pressure adjustment and a feedback control mechanism, the intelligence and precision of dynamic pressure control of the strapping machine are improved.

The invention relates to the field of industrial automation, in particular to a multi-camera vision stacking pose planning method and system for an intelligent loading and unloading robot. The method comprises the following steps: constructing a collaborative sensing system through a plurality of industrial cameras deployed in a target space, and collecting dynamic environment data of a stacking area in real time; generating a self-adaptive stacking pose based on a hierarchical pose planning mechanism: analyzing an initial pose parameter through a theme control layer and generating a preliminary placement instruction, and verifying the feasibility of the preliminary placement instruction based on environmental data of the collaborative awareness system through a visual verification layer, and a final placement coordinate is optimized by combining the accurate positioning layer with a virtual box matching algorithm. The problems that in the prior art, real-time environment sensing capacity is lacked, pose planning is disjointed with the actual environment, and dynamic change scenes cannot be processed are solved.

The invention discloses an intelligent hardware grinding system based on machine vision, which comprises a machine vision module used for carrying out image acquisition on grinding of hardware and generating surface feature information and grinding state image feature information of the hardware; the robot grinding module is used for grinding the hardware according to the surface feature information and the grinding state image feature information; the control module is connected with the machine vision module and the robot grinding module and used for adjusting grinding equipment control instruction features and grinding parameters in real time according to the surface feature information and the grinding state image information; according to the method, the target hardware grinding information is subjected to image recognition, the image description set is mined, and accurate path planning is generated and covers shape, size, defect position and other information. According to the method, deviation judgment is carried out on the multiple grinding task events, so that the deviation correction execution strategy is determined, the hardware grinding precision is effectively improved, the hardware rejection rate is reduced, and the hardware production efficiency is improved.

The invention provides a cobblestone stratum bored pile construction and drilling parameter intelligent control method, and relates to the technical field of artificial intelligence and bored pile construction, and the method comprises the following steps: arranging a sound wave emission array at the end part of a drill bit to collect cobblestone distribution information, identifying a weak connecting band as a passable area, calculating an optimal obstacle avoidance track, and setting a posture control point; and drill bit displacement, slurry injection and drill rod deformation parameters are adjusted, so that the drilling tool can intelligently pass along the obstacle avoidance track. Large cobblestones can be effectively avoided, the drilling resistance is reduced, the drilling efficiency is improved, and equipment abrasion is reduced.

A robot in accordance with at least some embodiments of the present technology includes a neck region through which the robot is configured to transmit and receive light. The robot defines a robot height and includes a body, a head carried by the body, and a neck extending between the head and the body along the robot height. The robot further includes a structural neck frame at a periphery of the neck in a plane perpendicular to the robot height. The structural neck frame defines windows distributed around the periphery of the neck. The robot further includes a sensor disposed at least partially within the structural neck frame. The sensor includes a laser configured to transmit light via the windows and a detector configured to receive light via the windows. A field of view of the sensor extends at least 320 degrees around the neck.

The invention discloses a heading equipment cutting head position calibration method based on image acquisition, which comprises the following steps: S1, acquiring image data and preprocessing the image data; s2, extracting cutting head feature points, and constructing a two-dimensional feature point set; s3, calculating a three-dimensional coordinate by using perspective transformation, and generating a point cloud set; s4, performing rigid registration on the point cloud set and a standard structure model of the tunneling equipment, and iteratively solving a rotation matrix and a translation vector to obtain pose parameters; s5, simulating change tracks of the feature points in continuous frames, constructing a time consistency constraint, and optimizing pose parameters; s6, the optimized three-dimensional coordinates are converted to a reference coordinate system, space alignment is completed, and a position calibration result is generated; and S7, outputting a calibration result for control instruction generation and path planning. According to the invention, high-precision and non-contact three-dimensional position calibration of the cutting head of the tunneling equipment is realized, and operation automation and control precision are improved.

The invention discloses a control method applied to self-piercing riveting, and relates to the technical field of self-piercing riveting control. According to the method, riveting material data are collected in real time through a multi-source data fusion interface, the high-dynamic deformation process of a riveting head is captured, deformation rate and rebound value characteristic values are extracted, and a multi-dimensional process parameter set is constructed. And comprehensively analyzing the hardness, thickness and plastic dissipation characteristics of the material, and establishing an anti-deformation capability evaluation function. By introducing the fluctuation characteristics of the punching force, the nonlinear relation between the punching force and the elastic deformation of the riveting rod is analyzed, a hybrid compensation model is constructed, and a riveting dynamic coupling compensation vector is output. And generating a compensation weight matrix through an adaptive optimization algorithm, and dynamically adjusting the stamping force and the displacement of the riveting rod in combination with an anti-saturation control strategy. And dynamically adjusting a gain parameter through multi-scale filtering and a Lyapunov stability criterion, and triggering iterative updating of a compensation weight parameter during out-of-tolerance so as to optimize a control effect. Riveting precision and stability are improved, and the service life of equipment is prolonged.

The invention relates to the technical field of intelligent printing and industrial automation control, and discloses an intelligent label printing optimization system, method and device based on image recognition. The method comprises the following steps: constructing an object surface feature matrix according to surface three-dimensional point cloud data and texture information of a to-be-labeled object; performing regional adaptability evaluation on the object surface feature matrix to obtain a thermodynamic map so as to determine a target labeling region; obtaining semantic information corresponding to preset label contents to generate typesetting constraint conditions corresponding to the label contents; generating an optimized typesetting scheme corresponding to the label content according to the typesetting constraint condition, and controlling preset printing equipment to print according to the optimized typesetting scheme to form a target label; and according to the first pose information corresponding to the object to be labeled, the preset second pose information of the printing equipment and the area range corresponding to the target area, a preset movement track corresponding to the mechanical arm is generated, and the mechanical arm is controlled to paste the target label to the target area according to the movement track.

The invention relates to the technical field of stamping part surface detection, in particular to a stamping part surface detection method and a welding slag cleaning device.The detection method is based on three-dimensional point cloud data processing, is not affected by environment light changes, can more accurately separate a defect area from a background, and is high in detection accuracy. The welding slag can be effectively identified even at a complex geometrical shape or a deep concave position, comprehensive detection of a stamping part with a complex shape can be realized, and the accuracy and the efficiency of detection are remarkably improved; by presetting the basic threshold value and dynamically adjusting according to the reflection characteristics, it can be guaranteed that the stamping part can obtain stable detection and cleaning results under the detection conditions of different light environments.

The invention relates to the technical field of image processing, and discloses an automobile decorative plate gluing positioning method. The method comprises the following steps: acquiring a decorative plate image, identifying a contour to determine a gluing area, and detecting a material to select an adhesive; setting a reference point to calculate position deviation, and adjusting the position if the deviation is greater than a threshold value; environment temperature and humidity are detected and adjusted, and the surface of the gluing area is activated; generating a track to control coating, and adjusting parameters if the detection uniformity is low; glue distribution is analyzed, and curing parameters are set according to glue types to reach the standard. According to the automobile decorative plates made of different materials, based on material characteristic data and adhesive curing characteristics, self-adaptive accurate gluing positioning and differential curing treatment are achieved, and the quality stability and production efficiency of decorative plate bonding are improved.

The invention discloses a laser-arc hybrid welding interface temperature regulation and control method and system with an external magnetic field. The method comprises the steps that current welding parameters of a welding sample are obtained; an interface temperature distribution feature neural network prediction model is adopted to process the welding parameters, and current temperature distribution features of the welding interface are obtained through prediction; based on the current temperature distribution characteristics of the welding interface and the standard temperature distribution characteristics of the welding interface, the deviation value of the current temperature distribution characteristics of the welding interface is determined; based on the deviation value, determining the adjustment amount of the magnetic field intensity of the induction coil through a fuzzy rule; and based on the adjustment amount of the magnetic field intensity of the induction coil, the magnetic field intensity of the induction coil is adjusted so as to adjust the current temperature of the welding interface.

The invention discloses a terminal crimping quality detection method and system, and relates to the technical field of terminal crimping image detection. Comprising the steps that space coordinates of a standard datum point in a crimping image are determined, and the standard datum point is used for representing the space coordinate position, meeting the standard terminal crimping inspection standard, between a corresponding wire and a terminal notch. According to the method, the crimping samples which do not meet the standard terminal crimping inspection standard are rapidly removed in a spatial positioning mode, and then the crimping sample thermal imaging images which do not meet the standard terminal crimping inspection standard are obtained on the crimping surfaces of the crimping samples by means of trigger logic. According to the method, the crimping samples are detected, the invisible faults of the crimping samples are judged based on the set standard terminal crimping inspection standard, and finally different commands are input to the crimping equipment according to the types and severity levels of the invisible faults, so that the rapid detection of the crimping samples and the dynamic adjustment of the crimping equipment are realized, and the stability of the monitoring dimension of the crimping quality is ensured.

The invention discloses a grooving machine rigidity dynamic adjusting system and method based on material image recognition, and relates to the technical field of grooving machine rigidity dynamic adjusting, and the method comprises the following steps: obtaining a material surface and subsurface image sequence of a grooving machine processing area; inputting the image sequence into a pre-trained depth vision analysis model, and outputting a material characteristic parameter set in real time; converting the material characteristic parameter set into a target rigidity value based on a rigidity demand mapping model; within a preset regulation and control window period before the cutter makes contact with the target machining area, the initial rigidity adjustment amount is obtained according to the target rigidity value, and a rigidity adjustment instruction is generated and sent to a rigidity adjustment execution mechanism for dynamic adjustment; in the cutting process, fusion of feedback data and an image analysis result is obtained, and the initial rigidity adjustment amount is corrected; dynamic, accurate and predictive active adjustment of the rigidity of the grooving machine is achieved, and therefore the machining adaptability, intelligence and stability of the grooving machine are effectively improved.

The invention discloses a method and system for polishing the surface of a steel pipe coated with a stainless steel pipe, and relates to the technical field of steel pipe grinding machining.The method comprises the steps that point cloud data flow and image data flow are input into a defect recognition channel to be recognized, and defect information is positioned; the target steel pipe three-dimensional framework is compared to determine the target grinding workload; dividing the target polishing workload to obtain a target working interval sequence; optimization is carried out based on the pipe data and the expected polishing indexes, and optimized polishing parameters are determined; and mapping calculation is conducted based on the pipe wall interval width and the interval grinding thickness, and a feeding speed change sequence is generated to execute steel pipe rough grinding machining. The technical problems that in the prior art, the steel pipe surface coarse grinding precision is low, and the steel pipe surface coarse grinding quality and the steel pipe surface coarse grinding efficiency are poor due to the fact that the steel pipe coarse grinding feeding speed is low in adaptation degree with the steel pipe surface state are solved, and the steel pipe surface coarse grinding efficiency is improved by improving the steel pipe coarse grinding feeding speed and the steel pipe surface state adaptation degree. The technical effect of improving the precision of rough grinding machining of the surface of the steel pipe is achieved.

The invention relates to the technical field of spraying control, in particular to a control system of an intelligent robot for spraying automobile clothing and a control method and application of the control system, the control method and the application are applied to the intelligent robot, and the intelligent robot comprises a robot body, a scanning assembly and a spraying assembly; the control system comprises a scanning analysis unit which is used for controlling the scanning assembly to carry out omnibearing scanning and analysis on a target vehicle to obtain vehicle three-dimensional shape parameters, vehicle model information and damaged area characteristics; and the spraying planning unit is used for calling a preset vehicle type spraying template according to the vehicle three-dimensional shape parameters and the vehicle type information to determine an initial spraying path. The deviation in the spraying process is monitored in real time and optimized and adjusted, the situation of uneven thickness or incomplete coverage generated in the spraying process can be effectively avoided, and it is ensured that the spraying quality reaches the expected standard.

The invention discloses a video double-gun welding path planning control method based on synchronous visual identification, and particularly relates to the technical field of multi-welding-gun collaborative welding, cross-equipment time alignment is realized through multi-angle image acquisition, a synchronous video frame sequence is constructed, a welding seam boundary is identified, and a change track is generated; predicting path conflicts and planning non-interference paths in combination with the initial posture of the welding gun and the space parameters; a time scheduling model is constructed to execute beat dislocation control, and in the welding process, videos and electric arc feedback signals are collected, track offset is judged, the posture, the position and the compensation speed are dynamically corrected according to the track offset, and closed-loop control and synchronous execution are completed; according to the method, the image time consistency is improved through multi-angle video frame synchronous construction, and the welding seam track recognition precision is improved; introducing double-welding-gun path prediction and conflict analysis, and planning a non-interference path combination; and video and arc signal closed-loop adjustment is combined, dynamic synchronous correction of the path posture and the speed is achieved, and the welding stability and precision are guaranteed.

The invention discloses an action space determination method and device of an intelligent agent, equipment and a storage medium, and relates to the field of artificial intelligence and machine learning. The method comprises the steps of determining target high-resolution visual features of a target object according to a collected time sequence picture of the target object based on a high-resolution visual model; determining target global visual features of the target object according to the time sequence picture based on a global visual model; preprocessing the initial noise, the initial diffusion step length and the historical time sequence action sequence of the target agent to obtain a target noise variable, a target diffusion step length and a target time sequence action sequence; and based on a multi-modal diffusion model and a decision diffusion model, according to the target high-resolution visual feature, the target noise variable, the target global visual feature, the target diffusion step length and the target time sequence action sequence, determining a target action space of the target agent. According to the technical characteristics, the accuracy and the reliability of determining the action space can be improved.

The invention discloses a railway cargo grabbing method based on improved YOLO and depth map processing, and the method comprises the steps: collecting a color image and a depth image of a target scene through a camera, inputting the color image into an improved YOLOv8 model, and obtaining a mask image; performing registration processing on the mask image by using the depth image to obtain a plurality of alternative target areas; performing three-dimensional statistical analysis on each alternative target area, and screening all the alternative target areas to obtain an effective target area; and selecting a plurality of candidate edge points in the effective target area, performing screening according to the score of each candidate edge point, and obtaining a grabbed area according to the screened candidate edge points. According to the embodiment of the invention, accurate identification and positioning can be carried out on railway goods in a complex scene, so that the robot grabbing efficiency and success rate in a railway freight scene are improved.

The invention relates to the technical field of grinding and polishing parameter regulation and control, in particular to an ultrahigh-precision microsphere integrated grinding and polishing method and system based on self-adaptive control, and the method comprises the steps: constructing a grinding and polishing platform, obtaining grinding microspheres according to grinding and polishing parameters and by utilizing the grinding and polishing platform, carrying out the grinding process analysis of the grinding microspheres, obtaining grinding process factors, and obtaining the grinding process factors; judging whether the grinding process factor is smaller than a standard process factor, if not, obtaining a complete grinding parameter set, if yes, calculating a grinding damage factor, judging whether the grinding damage factor is smaller than a standard damage factor, if yes, obtaining a process grinding parameter set, and if not, obtaining a damage grinding parameter set; and a self-adaptive control model is constructed according to the complete grinding parameter set, the process grinding parameter set and the damage grinding parameter set. According to the invention, the precision and efficiency of integrated grinding and polishing of ultrahigh-precision microspheres can be improved.

Dynamic pick pose recovery is described. The concepts can be relied upon to determine the pose of an item during a process for picking, moving, and placing the item among totes, or other uses. In one example, an item can be picked using a robotic arm, and the item can be repositioned for placement at a second location. Images of the item can be captured as the item moves. The images can be segmented to determine masks of the item. The masks can be projected into a point cloud within a bounding volume, to generate contours. Points of the point cloud that are positioned outside the contours can be discarded, to find a subset of points representative of a pose of the item. The position and orientation of the item can be calculated, for placement of the item at a second location, based on the pose of the item.

The embodiment of the invention relates to the technical field of image processing and positioning, in particular to a processing and positioning method and system for adaptive image recognition, and the method comprises the steps: obtaining a multi-source image data set of a target processing scene; performing image state adaptability analysis processing on the original image sequence to obtain an image recognition feature set of each image region in the original image sequence; performing positioning state mapping processing on the image recognition feature set based on the equipment positioning state data set, and generating a spatial positioning driving feature set corresponding to each image region; and generating a self-adaptive positioning control instruction according to the spatial positioning driving feature set, transmitting the self-adaptive positioning control instruction to an execution end of the processing equipment, and indicating the processing equipment to execute self-adaptive pose positioning control operation for the current image area. Therefore, the flexibility of processing equipment to cope with complex processing scenes is greatly improved, and it is ensured that target processing operation is accurately executed under various observation poses and environmental conditions.

The invention discloses a shoe tree grabbing robot track planning system and method based on multi-modal sensing. The system comprises a shoe tree storage area, a mechanical arm grabbing assembly, a multi-modal sensing device, a posture recognition module, an interference sensing module, a grabbing point optimization module, a stable window generation module, a path planning module, a fine adjustment control module and a self-learning module. The system extracts the posture of the shoe tree by fusing visual images, structural sound waves and infrared contour information, then utilizes interference fringes to analyze and judge the material and friction characteristics, combines stability to judge and screen a grabbable target, and executes posture fine adjustment and fitting at the tail end of a clamping jaw through a touch sensing film. And the grabbing failure information is used for updating the strategy database to realize self-adaptive optimization of the grabbing strategy. The method is suitable for grabbing special-shaped objects and is high in robustness and success rate.

The invention discloses a self-adaptive hippophae rhamnoides harvesting device based on machine vision, relates to the technical field of hippophae rhamnoides harvesting, and solves the problems that the hippophae rhamnoides harvesting device is insufficient in intelligence, the position of each mechanism cannot be adjusted in real time according to the state of branches, and trees are easily damaged. The upper portion of the folding mechanism is connected with the conveying mechanism through a hydraulic folding machine, the height adjusting mechanism is arranged on the portion, at the front end of the conveying mechanism, of the support, the upper end of the height adjusting mechanism is connected with the branch shifting mechanism, and the lower end of the height adjusting mechanism is connected with the cutting mechanism and the branch gathering mechanism. The growth condition and the lodging condition of branches and the distribution condition of sea buckthorn fruits can be determined through image recognition, the opening and closing angle between the branch gathering plates on the left side and the right side, the height of the knife rest and the height and the extension length of the branch shifting wheels are automatically adjusted according to feedback data, and the automatic and efficient harvesting device is suitable for automatic and efficient harvesting of the sea buckthorn fruits.