17results about How to "Improve grasping accuracy" patented technology

The utility model relates to the technical field of automobile parts, in particular to a fin product array and steering collecting machine. According to the technical scheme, the device comprises a collecting table, a feeding table and push plates, the collecting table is connected with the feeding table, a conveying belt is arranged on the feeding table in a transmission mode, the push plates are arranged above the conveying belt in a sliding mode through air cylinders, work waiting positions are arranged on the conveying belt through splitter plates, a main body beam is arranged on the side of the collecting table, and the main body beam is connected with the collecting table. A horizontal arm is horizontally and slidably arranged on the main body beam, a vertical arm is vertically and slidably arranged on the horizontal arm, swing tables are rotatably arranged on the lower surface of the vertical arm at equal intervals, vacuum suction cups are arranged on the lower surfaces of the swing tables, and a stock bin is arranged on the side, away from the conveying belt, of the collecting table. According to the utility model, ordered array of fin products is realized through cooperation of structures, and suction, directional steering and accurate release of the products are realized through the suction mechanism with a multi-degree-of-freedom moving structure and the rotary swing table.

The utility model relates to the technical field of the automatic production to power board especially, it is a kind of equipment of automatic identification feed position and intelligent grabbing and assembly, it includes: feed arrangement, receives and stores spare parts temporarily;Conveying device, receives and stores box;Grabbing device, grabs, shifts and assembles spare parts in box;And identification system, to spare parts and box are automatically identified, assist grabbing device to complete the grabbing, shifting and assembly operation of spare parts;Wherein, identification system is equipped with top identification module, the top identification module is installed in the upper of feed arrangement, and the spare parts temporarily stored on feed arrangement are automatically identified, to assist grabbing device to carry out intelligent grabbing operation to spare parts.Summarized above, through multiple identification module accurate positioning spare parts, feed conveying structure optimization, reliable gripping jaw assembly grabs assembly, effectively improve grabbing efficiency, assembly quality, reduce manual intervention, reduce cost, enhance equipment applicability and competitiveness.

The invention relates to a ball head rod disordered grabbing method based on 3D vision, belongs to the technical field of robot operation and automatic manufacturing, and particularly relates to a workpiece pose estimation method based on combination of YOLOv8 and Triplet Attention modules, which is used for disordered grabbing tasks in complex scenes. According to the method, the color and depth images of the workpiece are acquired through the RGB-D camera, and the efficient lightweight Triplet Attention module is introduced, so that the processing speed and precision of the model on the target detection and segmentation task on the mobile terminal equipment are remarkably improved. And the Triplet Attention module enhances the space attention mechanism of the model through three-way rotation convolution operation on the features, so that the detection and segmentation precision is remarkably improved. The segmented mask region is applied to the depth image, corresponding point cloud data are extracted, and six-degree-of-freedom pose estimation is carried out by using a normal consistency optimization (NDT) algorithm. The NDT algorithm is excellent in processing noise and partially shielded scenes. Experimental results show that compared with an original YOLOv8 model, the model added with the Triplet Attention module is improved in segmentation precision and recognition accuracy. The method has high accuracy and robustness in the aspects of workpiece recognition and pose estimation, and is suitable for real-time industrial application scenes.

This utility model relates to the field of fruit processing technology, and in particular to a high-efficiency peeling and pitting device for fruit processing, including a fixed plate; it also includes a fruit positioning block and a peeling and pitting assembly; a support frame is fixedly connected to the lower end of the fixed plate, a mounting frame is fixedly connected to the upper end of the fixed plate, the peeling and pitting assembly is provided on one side of the fixed plate, the fruit positioning block is fixedly connected to the upper end of the fixed plate, a first telescopic cylinder is fixedly connected to the lower end of the fixed plate, and a movable plate is fixedly connected to the output end of the first telescopic cylinder; this device works by placing the fruit on the fruit positioning block, activating the first telescopic cylinder, which drives the movable plate to slide, the movable plate to move the toothed plate, the toothed plate to rotate the gear, thereby causing the two sets of movable plates to move together, the movable plate to move the connecting plate, and the connecting plate to move the V-shaped clamping block, thereby clamping and fixing the fruit, preventing the fruit from slipping or shifting position during the gripping process, improving gripping accuracy, processing quality and efficiency.

The application discloses a multi-modal depth perception and grasping system based on transparent objects, and relates to the field of robot operation, comprising a multi-spectral perception module, a depth correction module, a grasping posture generation module and a control module. The application comprehensively acquires visual information and thermal radiation information of the transparent object by combining two perception methods of RGB-D image and thermal imaging (TIR) image, and analyzes systematic errors of the depth map to detect error sources of the RGB-D camera and the TIR camera. The system adopts an encoder-decoder model as a depth correction core, the model extracts complementary features of the RGB-D image and the TIR image through a modal exclusive encoder, and utilizes a feature fusion module to complete feature alignment and integration, thereby effectively improving the depth estimation accuracy on the transparent surface. Meanwhile, a Bayesian optimization method is adopted to optimize hyperparameters of the depth correction model, through hyperparameter optimization and model fitting processing, the system effectively avoids overfitting and underfitting problems, and further improves the robustness of the depth correction model and the grasping accuracy of the transparent object.

This invention relates to the field of robotic arm control technology, specifically a control system and method for a chemical emergency robotic arm based on intelligent perception. The system includes: a data acquisition unit for collecting environmental data from a chemical scenario and obtaining an initial depth image of the target area of ​​the chemical equipment to be operated; performing multi-sensor fusion processing on the environmental data and the initial depth image to obtain corresponding gas concentration information, obstacle location information, and image data of the target area; and a hazard assessment unit for inputting the gas concentration information, obstacle location information, and the current posture information of the robotic arm into a hazard assessment model to obtain the corresponding operational hazard level and the distance to the nearest obstacle. This invention uses a target recognition model to accurately obtain the location information of the target area and combines this with data such as the operational hazard level and obstacle location information to generate obstacle avoidance paths and operational instructions. This enables the robotic arm to intelligently avoid obstacles in complex environments while ensuring smooth operation.

This utility model relates to the field of forging press technology, and in particular to a high-precision center-positioning fast forging press. Technical solution: The high-precision center-positioning fast forging press includes a forging press and a positioning and feeding assembly. A positioning and feeding assembly is located at the front of the forging press. This utility model uses a second lifting cylinder below both ends of an anti-slip clamping plate to drive its lifting and lowering. The descending anti-slip clamping plate presses down and clamps one end of the workpiece above the feeding table. Combined with a lifting screw mechanism and a horizontal adjusting screw rail to adjust the position of the horizontal adjusting suction cup, the suction cup descends to vacuum-adhere and grab the workpiece. The precise transmission characteristics of the screw are used to achieve the workpiece positioning function during material grabbing, thus ensuring the placement accuracy of the workpiece when it is transported to the forging press station by the suction cup.

The application provides a kind of object scanning data correction method, grabbing system control method, grabbing system and computer readable storage medium, wherein the object scanning data correction method includes: obtaining the scanning data of a feature surface in an object, the object has an ideal shape, under the ideal shape, the scanning shape of the feature surface is a closed figure, and there is no acute angle in the internal angle of the closed figure;The scanning data is converted into a plan view by vertical projection;Obtain the inscribed figure of the feature surface plan view of the object, the inscribed figure is similar to the shape of the feature surface in the ideal shape of the object;Calculate to obtain a correction model, the correction model is similar to the ideal shape of the object.The embodiments of the application utilize the inscribed figure similar to the ideal shape of the object to calculate and obtain the correction model of the object, and the correction model is used for subsequent processing process.The correction model can overcome the problem of inaccurate positioning and shape deformation edge corner loss, and improve the accuracy of object scanning data.

A system and method for moving a payload, the system comprising: an aircraft device having a housing provided with one or more air propulsion units; the housing of the correction device is provided with one or more air propulsion units configured to enable the correction device to move relative to the aircraft device, the housing of the aircraft device and the housing of the correction device are coupled to each other through a telescopic flexible connecting rod, the correction device is provided with a docking module, and the docking module is used for docking the aircraft device and the correction device. The docking module is mounted on at least one or more retractable rigid connecting rods and configured to be removably coupled to a housing of a payload, and the system further includes a control device configured to vary the extent of extension of the flexible connecting rods and to vary the extent of extension of the rigid connecting rods.

The invention relates to the technical field of manipulator control, in particular to a chemical emergency manipulator control system and method based on intelligent perception, and the system comprises a data collection unit which is used for collecting the environment data of a chemical scene, and obtaining an initial depth image of a target region of to-be-operated chemical equipment; performing multi-sensor fusion processing on the environment data and the initial depth image to obtain corresponding gas concentration information, obstacle position information and image data of the target area; and the danger evaluation unit is used for inputting the gas concentration information, the obstacle position information and the current posture information of the manipulator into a danger evaluation model to obtain a corresponding operation danger level and a nearest obstacle distance. According to the method, the target recognition model is adopted to accurately obtain the position information of the target area, and the obstacle avoidance path and the operation instruction are generated in combination with data such as the operation danger level and the obstacle position information, so that the manipulator can intelligently avoid obstacles in a complex environment, and meanwhile, smooth operation is ensured.

The utility model relates to automobile parts clamping mechanism technical field, concretely relates to a kind of elastic clamping's automobile parts quick positioning clamping mechanism, including outer frame and arc clamp, the inner wall of outer frame is symmetrically provided with guide slot one, the inside of two guide slot one is slidably clamped with guide plate, two between the guide plate are fixedly connected with guide rod.The utility model is through the setting and the cooperation of guide rod, guide slide block, spring, vertical block, electric push rod and arc clamp, the elastic quick clamping of automobile parts can be carried out, to make installation and disassembly more convenient, wherein through the setting of servo motor one, unidirectional screw, guide sleeve, slide bar and the cooperation of guide plate along guide slot one sliding can limit the front and back position of arc clamp clamping, through the setting of servo motor two, bidirectional screw, moving block and connecting rod two and the cooperation of lifting plate along guide slot two sliding effect, the height position of automobile parts placed on lifting plate can be limit auxiliary control.

The application relates to the technical field of underwater robots and discloses a rope-driven mechanical arm and underwater underwater vehicle, which comprises a mounting seat, a mechanical arm mechanism, a paw mechanism and a driving mechanism. The mechanical arm mechanism comprises a first connecting arm, a first parallel arm, a second parallel arm, a second connecting arm and a plurality of hinge pieces. One end of the first connecting arm is connected with the mounting seat, one end of the first parallel arm and the second parallel arm is hingedly connected with the other end of the first connecting arm, the other end of the first parallel arm and the second parallel arm is hingedly connected with one end of the second connecting arm, and wiring channels are arranged on the first connecting arm, the second connecting arm, the first parallel arm and the second parallel arm. The connecting end of the paw mechanism is connected with the other end of the second connecting arm. The driving mechanism is arranged on the mounting seat. The application can improve the structural stability and action control precision of the mechanical arm and improve the grasping precision of the target object.

The invention discloses a robust grabbing detection method for monocrystalline silicon. The robust grabbing detection method comprises the following steps: S1, acquiring an RGB-D image containing a monocrystalline silicon target to be grabbed; s2, performing weighted fusion on the RGB image and the depth image to generate a fused image; s3, inputting the RGB-D image into a pre-trained end-to-end grabbing detection network, and outputting an initial grabbing posture and an initial quality image; s4, performing double-layer geometric structure feature extraction based on the fused image; s5, executing a grabbing process, and judging whether an improvement condition is met or not; s6, if the improvement condition is met, a final improved grabbing posture is output; the method has the advantages that visual noise interference caused by high light reflection of the material surface is effectively overcome, and edge grabbing deviation of the deep learning model is forcibly corrected by using geometric center information, so that grabbing precision, stability and safety of automatic sorting of monocrystalline silicon are remarkably improved.

An automatic tobacco leaf feeding device based on vision assistance includes a positioning column, a horizontal moving device, a vertical moving device, a controller, a three-axis robotic arm, and a robotic gripper. Its key feature is that: binocular cameras are symmetrically arranged on both sides of the horizontal support of the horizontal moving device, with the distance between the two horizontal supports being the width of two tobacco baskets; a laser rangefinder is located in the middle of the vertical support of the vertical moving device; the binocular cameras and the laser rangefinder are connected to the controller via data cables; and the robotic gripper can rotate in a horizontal position. This invention improves feeding efficiency and accuracy through the visual assistance of the binocular cameras and the laser rangefinder, and can accurately grasp tobacco leaves when there is little remaining material. It can also grasp two tobacco baskets simultaneously, allowing both baskets to enter and exit at the same time. The most significant feature of this invention is that it achieves uninterrupted automatic feeding of tobacco leaves into two baskets, reducing the labor intensity of workers and improving work efficiency.

The utility model relates to a trussed material mechanical arm grabbing mechanism for dye conveying, which belongs to the technical field of manufacturing of automatic dye conveying machines in printing and dyeing workshops and comprises a conveying truss, a dye material barrel bin frame is arranged on one side or two sides of the conveying truss, and an X-axis walking trolley is arranged on the conveying truss. The X-axis walking trolley is provided with a clamping jaw rotating arm for clamping the dye barrel bin frame, a Y-axis lifter is arranged between the clamping jaw rotating arm and the X-axis walking trolley, and a Z-axis left-right displacement driver is arranged between the X-axis walking trolley and the Y-axis lifter. The clamping jaw rotating arm comprises an air cylinder clamping jaw, and a rotating arm is arranged between the air cylinder clamping jaw and the Y-axis lifter. Based on a right-angle X, Y and Z three-coordinate-axis system, the position and track of the workpiece can be accurately adjusted, manual intervention is reduced through automatic grabbing and conveying, and the production efficiency is improved. Compared with traditional manual operation, grabbing of the mechanical arm is more accurate, the problems of mistaken throwing and the like are avoided, and meanwhile the labor cost is reduced.

The present application relates to the technical field of toothbrush automatic manufacturing, and particularly discloses a self-adaptive gripping force control method and system of a mechanical hand of a toothbrush bristle planting machine, which comprises: starting a gripping material quality identification process, identifying a material quality area where a gripping area is located, if it is a transition area, outputting a material quality classification probability graph of the gripping area, executing a gripping contact action and collecting a contact force response signal, online identifying a local contact stiffness, integrating a material quality attribute vector, dynamically adjusting a normal impedance parameter, generating a normal flexible contact flag, if the normal flexible contact flag is received, collecting a three-axis torque signal at a gripping point, identifying a center of mass position vector of a toothbrush handle and calculating an eccentricity parameter, judging whether a tangential force active adjustment preparation mechanism is triggered, marking a control state, if the control state is tangential force to be intervened, calculating an expected tangential force target, introducing a friction force reserve observer to judge whether a normal force collaborative increase process is triggered, and executing tangential force adjustment.

The invention discloses a robot grabbing deviation correction method based on a 3D camera, and belongs to the technical field of industrial robot automatic control and vision measurement. Aiming at the problems of grabbing position offset and unstable round hole feature extraction caused by tray placement deviation, illumination variation and robot attitude error, the method comprises the following steps: collecting and positioning round hole point cloud at the tail end of a robot, realizing point cloud preprocessing by utilizing normal vector estimation, statistical filtering, clustering separation and edge extraction, and finishing coarse registration based on 4PCS; performing weighted fusion positioning on the circle center by combining GICP point cloud registration and RANSAC circle fitting; and then a perspective transformation matrix is constructed according to the final circle center and the theoretical circle center, and two-dimensional perspective correction is conducted on all grabbing point positions in the material disc. The center positioning stability and the overall grabbing precision can be improved under the complex working condition, and the manipulator is suitable for the fields of robot grabbing, material carrying, assembly positioning and the like in automatic production.