42 results about "Robot position" patented technology

This invention relates to the field of fault location technology and discloses a fault location method for a long-distance conveying inspection robot. The method includes: when the inspection robot performing long-distance conveying is detected to have reached an entrance equipped with an RFID tag, reading the RFID tag to determine the section of the long-distance conveying route to which the inspection robot belongs, and calculating the distance between the inspection robot and the entrance; acquiring an image of the idler roller taken by a camera mounted on the inspection robot, and using an image recognition algorithm to identify the idler roller code; when a fault signal is received, concatenating the section of the long-distance conveying route to which the inspection robot belongs, the distance between the inspection robot and the entrance, and the idler roller code identification result to obtain the position of the inspection robot in the long-distance conveying, and generating an alarm message. This invention combines RFID and visual recognition to accurately locate the inspection robot's position, improving positioning accuracy and thus improving fault handling efficiency.

A tetherless magnetic impact needle robot (MINRob) based on a triple-magnet system with reversible and repeatable magnetic collisions to overcome this constraint on output force. The working procedure of the system is divided into several states, and a mathematical model is developed to predict and optimize the force output. These force values in magnetic impact and penetration are obtained from a customized setup, indicating a 10-fold increase compared with existing miniature robots that only utilize magnetic attractive force. Eventually, the MINRob is integrated with a teleoperation system, enabling remote and precise control of the robot's position and orientation. The triple-magnet system offers promising locomotion patterns and penetration capacity via the notably increased force output, showing great potential in robot-assisted tissue penetration in minimally invasive healthcare.

The application discloses a kind of gas leakage identification positioning method and system suitable for mobile monitoring, belong to deep learning technical field.The method includes: through the microphone array on robot real-time acquisition sound signal on inspection path, input time attention module and frequency domain space attention module, obtain frequency domain space feature sequence after frequency domain space attention enhancement and time feature sequence after time attention enhancement, fusion obtains latent space feature;Based on latent space feature, multi-task gas leakage monitoring is carried out, and prediction classification result, distance prediction value and angle prediction value of gas leakage source are obtained;Effectively capture dynamic acoustic change related to robot position movement, improve identification and positioning accuracy.

This invention belongs to the field of photovoltaic automation technology and discloses a robotic pre-static curing warehouse. It includes several stationary positioning racks evenly distributed around the circumference, with a transport robot positioned at the center. The circular warehouse area formed by the stationary positioning racks has four directional channels for crystal tray / adhesive plate input rollers, crystal rod input rollers, cured material output rollers, and a maintenance channel. The transport robot has a multi-functional gripper at its end. The robotic pre-static curing warehouse solves the problems of long adhesive curing time, the need for material transfer after alignment, and low precision after bonding in existing technologies, while also improving space utilization and accelerating production cycle time.

The application relates to a rectangular recognition-based cluster robot position sensing system and method, and belongs to the field of robots. The system comprises a light sign module, a visual sensor module and a main control board, the main control board is connected with the light coding module and the visual sensor module. The method comprises the following steps: the main control board processes the image collected by the visual sensor, the processed image collected by the visual sensor is used to calculate the relative distance and angle of the neighbor robots and store the processed result into the storage unit of the main control board, the cluster algorithm program can be called, and the main control board controls power supply of the light sign module. The position information of the surrounding neighbors can be obtained by only loading a cheap camera module and a simple light sign module on the robot.

This invention relates to the field of automated production technology for square aluminum-cased lithium battery module PACKs for energy storage, and discloses an automated CCS installation device for energy storage modules. The device includes a enclosure, with a material-retrieving robot positioned in the center of the inner side of the enclosure. Inside the enclosure, on one side of the material-retrieving robot, are sequentially arranged a CCS-A hopper, a CCS-B hopper, and a CCS spacer foam hopper. Inside the enclosure, opposite the CCS-B hopper, is an assembly platform on which energy storage modules are placed. A secondary positioning platform is positioned inside the CCS-A hopper, between the CCS spacer foam hopper and the assembly platform. This invention, through a highly coordinated automated process, completely replaces the traditional manual identification, grasping, visual alignment, and pasting fixing operation mode. This not only stabilizes the installation cycle at a preset high-efficiency level, eliminating the speed bottleneck and instability of manual operation, but also directly reduces the manpower required for this workstation. This also achieves cost savings on auxiliary materials.

The application provides a robot positioning compensation system based on real-time feedback of mechanical arm end coordinates, the robot comprising a mechanical arm and an end effector, the end effector being arranged at the end of the mechanical arm; the positioning compensation system comprising a target ball, a laser tracker, a computer and a controller, the target ball being arranged on the end effector, a closed-loop control system being formed among the mechanical arm, the laser tracker, the computer and the controller; the laser tracker being used for detecting the coordinates of the target ball in real time and sending the coordinates to the computer, the computer being used for converting the coordinates of the target ball into the spatial coordinates of the mechanical arm and sending the spatial coordinates to the controller; the controller being used for generating a corresponding compensation signal according to the spatial coordinates and sending the compensation signal to the mechanical arm, and the mechanical arm moving to a set position according to the compensation signal.

The present application relates to a kind of humanoid robot OTA automatic upgrading method and system, it relates to the field of robot software maintenance, it includes: based on robot state information to determine target robot set;Batch upgrade task is issued to target robot set, and is installed and upgraded with silent installation method;Current battery capacity of robot is collected;If current battery capacity is lower than upgrade maintenance threshold, determine the nearest target charging area according to current robot position;Based on current robot position to determine idle robot, and control idle robot to carry current robot to target charging area and charge, while completing silent installation process in target charging area;After installation upgrade is completed, automatically run self-checking program to verify core function, when upgrade self-checking result meets the preset self-checking requirement result, mark the version information after upgrade as upgrade success and report to cloud management platform.The present application has the effect of improving the upgrading efficiency of robot.

This invention relates to the field of robot autonomous navigation technology, and provides a laser SLAM localization method and apparatus for scenes lacking geometric features. The method includes: acquiring an original point cloud collected in a target scene; creating a geometric point cloud map of the target scene based on the original point cloud; and creating a marked point cloud map based on the marked point cloud in the original point cloud; matching the real-time point cloud currently scanned by the robot with the geometric point cloud map to determine a geometric residual; matching the real-time marked point cloud in the real-time point cloud currently scanned by the robot with the marked point cloud map to determine a marked residual; determining a total residual based on the geometric residual, the marked residual, and their respective weights; and optimizing the total residual, determining the robot's current position as the position corresponding to the minimum total residual. This invention accurately determines the robot's current position by optimizing the total residual through a weighted average of the geometric residual and the marked residual.

The application relates to the technical field of building equipment, and discloses an automatic sizing robot for wall bricks, which is capable of moving along the surface of the wall bricks stably under the guidance of the directional wheels, and the wall bricks provide stable support for the robot when the robot moves along the wall bricks with the help of the directional wheels, the symmetrically distributed directional wheels form reliable guiding constraints with the side edges of the wall bricks, and the robot can only move along the predetermined track of the wall bricks, so that the robot position and the wall bricks are accurately aligned during the sizing process, the robot movement deviation phenomenon is effectively eliminated, and the accuracy and stability of the sizing operation are improved.

A machine vision inspection system (1) has digital data processors (25) linked with an articulated arm robot (15) supporting a camera and illuminator head (10) for capturing images form a scene over a machine bed (3). The head also includes a system-on-module with a GPU as an inspection processor located adjacent the camera sensor (120), but in a different chamber (109) of the head, separated by a chamber wall (123) from a camera chamber (108). The object may be three dimensional components in a manufacturing line, or product labels. The processors move the robot to pre-set camera positions and control image acquisition and scene illumination for each of a plurality of inspection points. During setup, the processors capture a pre-set robot position, preset camera settings, preset illumination parameters, and a natural language prompt for each of the plurality of inspection points. During runtime, for each inspection point the processors cause the robot (15) to move to the pre-set position for the inspection point when an object is in the camera scene (3) and activate the camera illuminator head to illuminate the scene and capture an image of the object. The inspection processor (140) then executes artificial intelligence code to analyse the image and determine results for the scene, generate an output for the inspection point in a format determined by the prompt associated with the inspection point during setup.

The application discloses a robot positioning updating method and device, electronic equipment and a readable storage medium, which are applied to a target robot carrying a laser sensor. The robot positioning updating method comprises the following steps: acquiring a current positioning point position of a corresponding laser positioning point in a global coordinate system at a current position, wherein the current positioning point position is converted according to a position conversion relationship between the laser sensor and the target robot; determining whether positioning updating is needed according to the current positioning point position; and if it is determined that the positioning updating is needed, performing positioning updating on a robot global position of the target robot by updating global position information of positioning points in a laser positioning point set. The application solves the technical problem of low positioning accuracy of the robot.

A method for providing a floor plan from images captured by a floor-moving robot, comprising: providing a camera mounted high enough in a robot housing to allow an inclined downward view of a floor; capturing a series of images of the floor with the camera; determining a position of the robot for each of the images; labeling each image in the series of images with a position of the robot at the time of image capture; cropping each of the images to identify at least one segment in each of the images; transforming the segment from a robot camera view into a planar view; filling the floor plan with each of the segments at the robot position in the planar view, with an offset corresponding to a difference between the robot position and the position of the segment on the floor; displaying the floor plan to a user;and accepting user input on the floor plan to change an operating property of the robot.;

The application discloses a goods automatic warehousing method and system for intelligent warehousing, and belongs to the technical field of intelligent warehousing. The method obtains dynamic event information such as goods elevator fault signal and robot position conflict detection data through a real-time data interface, constructs a dynamic path adaptive scheduling mechanism based on a path planning algorithm, and pre-provisions a path set, triggers an edge computing unit to complete a backup path calculation strategy within a system pre-provisioned time threshold when a dynamic event is detected, and finally controls the warehousing robot to execute a warehousing operation according to the planned path. The system comprises a data sensing module, a path planning module, an edge computing unit and an execution control module, and each module cooperates to realize real-time path optimization under dynamic events. The application effectively solves the problems of insufficient adaptability of dynamic scenes and low device cooperation efficiency in traditional warehousing, improves the warehousing efficiency and reduces the energy consumption.

Provided is a process including: receiving inspection path information indicating a path for a robot to travel, and a plurality of locations along the path to inspect; determining, based on information received via a location sensor, that a distance between a location of the robot and a first location of the plurality of locations is greater than a threshold distance; in response, causing a refrigeration system of an optical gas imaging (OGI) camera to decrease cooling; moving along the path; in response to determining that the robot is at a first location of the plurality of locations, sending a second command to the sensor system, wherein the second command causes the refrigeration system of the OGI camera to increase cooling; causing the sensor system to record a first video with an OGI camera; and causing the sensor system to store the first video in memory.

This invention discloses an insulator washing method based on the collaborative operation of two intelligent water-flushing robots. Specifically, the water-flushing robot positioned at the front identifies and locates the target insulator at the work site and acquires the distance information between itself and the target insulator. The three-dimensional coordinate information of the target insulator that meets the flushing distance requirements is saved. When the water-flushing robot positioned at the rear reaches the corresponding position of the front water-flushing robot, the saved target insulator coordinate information is transmitted to the control system of the rear water-flushing robot, adjusting the rotation of the flushing turret to achieve aimed flushing of the target insulator, thus completing the cleaning operation. This invention separates the target identification and positioning from the targeted flushing, completely avoiding the problem of water mist obstruction during the flushing process, effectively improving the accuracy of target insulator identification, and making the water-flushing robot's aimed flushing of the target insulator more accurate and stable.

The utility model discloses a kind of orthopedic surgery robot positioning devices of multi-degree-of-freedom mechanical arm, the device includes bed body, positioning base plate, surgical mechanical arm and optical camera. Positioning base plate is composed of trunk fixed plate and lower limb positioning plate, and several groups of fastening belts are slidably arranged on the lower limb positioning plate for fixing the lower limbs of patients. The surgical mechanical arm is connected with the bed body through a ball screw drive mechanism, and an optical camera for capturing the markers of the lower limbs of patients is arranged at the end. The device ensures the stability and safety during the operation through the high-precision laser positioning system and multi-degree-of-freedom mechanical arm, significantly improves the precision and success rate of the operation, and reduces the operation time and the risk of postoperative complications.

The application discloses a focused ultrasound stimulation system and a control method for regulating liver metabolism, and the system comprises a focused ultrasound transducer, a robot positioning module, an image navigation module and a control module. The image navigation module acquires an ultrasound image of a target region, identifies feature points of a hepatic portal region and generates target point coordinates. The robot positioning module carries and moves the focused ultrasound transducer. The control module controls the robot positioning module to dynamically move the focused ultrasound transducer according to the real-time updated target point coordinates, so that the focal domain of the focused ultrasound transducer coincides with the target region, and controls the focused ultrasound transducer to output low-intensity focused ultrasound. The application also provides application of low-intensity focused ultrasound in preparation of a device for treating non-alcoholic fatty liver disease. The system realizes non-invasive physical regulation of liver metabolism, effectively improves lipid deposition and inflammation state, and has the advantages of automation, precision and repeatability.

The application provides a micro cluster robot positioning and identifying device for an action capture system, which comprises a positioning plate body, a stand and a reflective marker point; the surface of the positioning plate body is divided into multiple point area categories according to a set rule, and a plurality of points are arranged in each point area category according to the set rule; the top of the stand or a stand combination is provided with the reflective marker point, and the stand or the stand combination can be installed in the point according to the set rule; and the stand has different lengths; the robot positioning and identifying code can be determined according to the point where the stand or the stand combination is installed and the length of the stand. The reflective marker point position code is realized by setting four types of resident point area and setting the height of the stand, and then the code is used as the individual code of the robot; in large-scale desktop cluster robot tests, the arrangement mode of the reflective marker point is not easy to be blocked, the code capacity is huge, and the robot positioning requirement of the large-scale desktop cluster robot test can be met.

The application provides a robot positioning mapping method based on a visual cortex and hippocampus space coding, and the method comprises the following steps: acquiring linear velocity and angular velocity through a wheel encoder and an inertial measurement unit, and obtaining robot pose information through path integration; collecting scene images by using a camera and extracting GIST features, obtaining a winning cell in a view cell network through Euclidean distance matching, updating weights, and introducing a posteriori entropy adaptive threshold to perform robust scene matching; storing the pose information and the successfully matched weight vector into a hippocampus CA1 area location cell, eliminating cumulative errors through iterative optimization, controlling the map size through space density redundancy pruning, and adopting a hierarchical switching strategy to perform scale stretching optimization, so that fast mapping is realized. Through simulating a biological space coding mechanism, the application improves scene recognition robustness, positioning consistency and mapping efficiency, and is suitable for intelligent navigation of a mobile robot.

A robot location planning method and apparatus based on reinforcement learning. The location planning method comprises: performing, by means of a preset positioning pen module, digital description on the location, shape and posture information of an object to be manipulated by means of a robot, so as to obtain digital object data; by using the digital object data as an input to a deep neural network of a simulation platform corresponding to the robot, and using, as an output, a manipulation location at which the robot controls the object, performing training to obtain an initial location planning model of the robot; on the basis of an application scenario of the object, selecting a corresponding observation space and task return logic to perform scenario optimization on the initial location planning model, so as to obtain a robot location planning model; and on the basis of the robot location planning model, predicting the digital object data of the object to be manipulated, so as to obtain a target location at which the robot manipulates the object to be manipulated. Therefore, on the basis of a trained robot location planning model, the robot planning accuracy meets the requirements of various industrial scenarios, and the workload involved in manual operations is greatly reduced.

A robot positioning measurement device (1) includes: a first position information acquisition unit (2) which acquires first position information when the robot is positioned in an arbitrary posture. The first position information is the three-dimensional command position of the tool tip point fixed to the front flange of the robot; a second position information acquisition unit (3) which acquires second position information in the above posture using a three-dimensional measuring device set in a predetermined measurement coordinate system. The second position information is the three-dimensional actual position of the tool tip point; and a coordinate system correction unit (4) which corrects the robot coordinate system, which serves as the reference for the robot's actions, so that the difference between the first position information and the second position information acquired when the robot is positioned in multiple different postures is reduced.

The present disclosure relates to the technical field of visual perception and robot motion planning, and provides a robot trajectory planning method and system under high visual visibility, which comprises: obtaining target object image data for target recognition to obtain the pose of the target object; performing robot trajectory planning based on Cartesian space according to the current position and target position of the robot to obtain a first planning trajectory; controlling the robot to move according to the first planning trajectory; constructing an optimization function of visual feedback, so that the detected target object is always within the camera field of view carried by the robot during the movement of the robot; and optimizing and correcting the planning trajectory according to the solution value of the optimization function, and controlling the robot to move according to the optimized trajectory. By constructing the optimization function, the target object is kept in the camera field of view during the movement of the robot, and the path is re-planned along with the movement of the target object, thereby improving the accuracy of grabbing the target object after the movement of the robot position and improving the success rate of grabbing the target.

The present application relates to the technical field of industrial robot polishing equipment, in particular to a multi-sensor fusion pneumatic constant force polishing device and polishing method, comprising a robot positioning module, a constant force execution module, a sensing detection module, a pneumatic control module, a polishing operation module, a control module and a protection assembly, a flange plate is fixed with a robot end effector to provide an installation base for each module; a moving plate slides along a linear guide rail, and a pneumatic cylinder provides power; multiple sensors cooperatively detect, and the pneumatic control module realizes stepless regulation and control of the pneumatic cylinder pressure; a polishing head is detachable, and the control module realizes multi-module cooperation. The present application overcomes the defects of the prior art through the technical solutions of multi-sensor fusion detection, pneumatic precise regulation and control and bias-free mechanical connection, and achieves significant beneficial effects in terms of technology, economy and use, and all effects are quantifiable through actual verification.

The application discloses a kind of based on FPGA's mine inspection robot vision servo control method, it is related to artificial intelligence vision technical field, including, pre-processing image data is input to the inference after training depth neural network model deployed on FPGA, generates target recognition result;With space-time attention method, target recognition result is fused with environmental sensor data in real time, dynamically adjusts the influence of space and time, generates after fusion multi-source sensor data;To the sensor data after fusion is carried out path planning and motion control, combines vision, laser radar and inertial measurement data, path optimization is carried out by Dijkstra algorithm, generates motion control instruction;According to smooth planning path, robot is driven by motion control instruction and moves, and real-time monitoring and acquisition robot position, speed and acceleration, generates execution feedback data.The application improves the accuracy and robustness of path planning and obstacle avoidance decision.

The application discloses a robot position determination reliability determination method, device and equipment and a storage medium. The method comprises the following steps: determining the Euclidean fitness score between the prior point cloud map and the target frame laser point cloud based on the normal distribution transformation positioning algorithm, the prior point cloud map and the initial pose of the robot; in response to the Euclidean fitness score meeting the preset convergence condition, determining that the Euclidean fitness score in the convergence state is a target Euclidean fitness score, and obtaining a target matching transformation probability value and a target matching parameter; determining the positioning reliability of the normal distribution transformation positioning algorithm for positioning the target frame laser point cloud based on the target matching transformation probability value and the target matching parameter; and determining the candidate position determination reliability based on the target Euclidean fitness score and the positioning reliability, normalizing the candidate position determination reliability, and obtaining the target position determination reliability. The application can improve the accuracy of robot position determination reliability determination and accurately reflect the reliability of robot positioning.

The application discloses a kind of visual mark robust positioning method and system for complex illumination environment, belong to robot positioning technical field, its technical scheme main point is including, obtain the current corresponding multi-source data set of inspection robot and carry out pre-processing, multi-source data set includes RGBD data and point cloud data;According to the laser composite feature matrix obtained according to pre-processed point cloud data;According to the visual composite feature matrix obtained according to pre-processed RGBD data and residual network model;According to laser composite feature matrix and visual composite feature matrix, obtain fusion matrix;According to the position of the current inspection robot where according to the fusion matrix corresponding to adjacent last time fusion matrix, the present application extracts visual composite feature matrix by means of residual network model, based on laser composite feature matrix, the geometric structure information of environment is completely retained, through the fusion of laser and visual composite feature matrix, improve the position perception accuracy of inspection robot in complex scene.

The application discloses a sterile operation method based on a vascular interventional robot technology and belongs to the technical field of medical instruments. The method is operated according to a standardized time sequence process, and comprises the steps of robot position determination, patient body position adjustment, patient disinfection, operating table sheet laying, robot sterile isolation, sterile accessory installation, operation execution, operation end, robot surface disinfection, robot storage and patient leaving the operating table. The application establishes the positioning correspondence relationship among the robot position, the patient body position and the sterile area of the operation, formulates a special sterile isolation operation method for the multi-joint mechanical arm of the robot and the operation end, standardizes the disinfection and sheet laying operation at the joint of the robot equipment and the patient operation area, and establishes the standardized steps of the post-operation robot sterile storage, so that the sterile control of the whole process of the vascular interventional operation robot operation is realized.