253 results about "Robot position" patented technology

The invention relates to the technical field of multi-sensor fusion positioning, and discloses an outdoor robot multi-sensor fusion method. Comprising the following steps that robot operation data are obtained through multiple sensors in the running process of a robot; taking the preprocessed operation data as measurement input of an unscented Kalman filter state estimation process, and obtaining first position data after fusion processing; learning the noise characteristics of each sensor by using a long-short-term memory network of a sliding window, and compensating the position deviation of the robot to obtain second position data; performing time synchronization processing on the first position data and the second position data, and inputting the first position data and the second position data into an improved double-layer multi-model adaptive estimation framework; the improved double-layer multi-model adaptive estimation framework adopts a double-layer structure; and obtaining final real-time position data. The method can inhibit noise and drift of a single sensor, reduces error accumulation caused by factors such as environment shielding, improves positioning precision, robustness and continuity, and is suitable for scenes such as outdoor driving robots.

A motion control method for an adaptive self-reconfigurable pipeline robot based on environmental perception includes: acquiring internal images of the pipeline for scene recognition, segmenting planar surfaces and curved surfaces in the images according to recognition results, and extracting boundary lines of the pipeline; calculating a straight-pipe width, a bent-pipe curvature, a slope angle, and a step height to analyze passability of the robot; designing a path planner and a swing-arm planner to generate a reference trajectory and a swing-arm angle sequence of the robot, performing smoothing, and inputting the reference trajectory and the swing-arm angle sequence into a model predictive control (MPC) motion controller; estimating a position and state of the robot through an Error State Kalman Filter (ESKF) algorithm, and inputting estimation results and collision warning signals into the MPC motion controller; and finally outputting a signal for control of a motor and a swing-arm motor.

The invention discloses a substation primary and secondary equipment communication prefabricated optical cable online monitoring method and system, and belongs to the technical field of communication prefabricated optical cable monitoring. The system comprises an optical cable parameter acquisition module, a communication quality evaluation module, a physical parameter analysis module, a first-aid repair path planning module and a fault database. The method comprises the following steps: optical cable parameter acquisition: acquiring data in real time, and converting high-dimensional data into low-dimensional data through a principal component analysis algorithm; communication quality evaluation: identifying communication characteristics in the low-dimensional signal parameter matrix based on a fuzzy comprehensive evaluation algorithm, and outputting a communication quality score; the physical parameter analysis module extracts physical deep features of the optical cable by using a deep belief network DBN, and inputs an improved Bayesian classifier to output a state classification result; according to the first-aid repair path planning, OTDR detection parameters are dynamically adjusted, and an optimal first-aid repair path is planned in combination with the position of the inspection robot; according to the invention, optical cable communication quality evaluation, accurate physical state classification and efficient fault repair planning are realized.

An autonomous warehouse robotics system integrates a multi-sensor platform, adaptive payload handling, dynamic task reallocation, advanced navigation, energy management, and comprehensive safety features into one mobile robot chassis. The system utilizes LiDAR, stereo vision, ultrasonic sensors, mmWave radar, thermal cameras, and event cameras to perform complete environmental sensing and obstacle detection. Sensor fusion combines adaptive weighting, multi-modal data integration, and statistical filtering to create high-confidence maps for reactive path planning and collision avoidance. The robot's payload system features machine vision for item recognition, telescopic lifts, variable-width grippers, and real-time toolhead verification to handle a variety of goods. Fleet management is achieved through dynamic task reallocation that considers robot location, battery level, and operational delays, all coordinated by a cross-platform middleware architecture that ensures standardized communication, remote monitoring, and over-the-air updates among diverse robot brands. Energy management optimizes power usage via predictive routing, autonomous return-to-charge, and auction-based scheduling. Safety is maintained through proximity detection, behavior-based intervention, and human-robot cohabitation protocols while advanced localization is enhanced by fusing ultra-wideband positioning with visual landmark alignment, inertial sensing, and machine learning to deliver high accuracy in non-line-of-sight conditions. An onboard edge AI module further refines navigation and task prioritization through neural network inference, ensuring robust, adaptive operation in dynamic, unstructured warehouse environments.

The invention relates to the technical field of pipe network leakage point positioning, and discloses a GIS-based pipe network leakage point high-precision positioning method and system, and the method comprises the steps: collecting a first camera image, a first infrared thermogram, first laser ranging data and first inertial measurement data through a detection robot; calculating a robot positioning track and constructing a pipeline structure model; detecting local coordinates of leakage points and creating a coded data packet; based on the first RTK-GPS coordinate of the initial inspection well, rotation transformation and ENU coordinate transformation are carried out on the local coordinate of the leakage point, drift correction is carried out when the leakage point arrives at the next inspection well, and the GIS coordinate of the leakage point is obtained; according to the method, the GIS coordinates and the coded data packets of the leakage points are used for generating a defect distribution visualization graph and a maintenance work order, the positioning error is reduced from the meter level to the centimeter level, accurate positioning of defects and automatic distribution of the maintenance work order are achieved, and the inspection cycle and the maintenance response time are shortened.

The invention discloses a multi-sensor cooperative robot target positioning system, and relates to the technical field of robot positioning, in particular to the multi-sensor cooperative robot target positioning system. The objective of the invention is to solve the problems of reduced positioning precision and insufficient robustness caused by sensor data failure, insufficient cooperation mechanism and motion interference in an extreme environment. The system comprises a multi-source sensing module, a collaborative fusion module, a motion modeling module and a closed-loop control module, a robot pose adjustment instruction is generated through multi-sensor data acquisition, space-time alignment and confidence weighted fusion, dynamic motion modeling and error compensation, and closed-loop collaboration of positioning and motion is achieved. According to the invention, the positioning precision, robustness and continuous operation capability of the system in an extreme environment are effectively improved.

The invention discloses an inspection positioning method, device and equipment for an inspection robot of a belt conveyor, relates to the technical field of inspection of belt conveyors, and can solve the technical problem that an existing rail-mounted robot is large in error in high-precision inspection positioning. Comprising the following steps: acquiring image video data of environment and equipment, acquiring initial parameter information of an inspection point according to the image video data, and drawing an inspection environment map model according to the image video data and the initial parameter information of the inspection point based on calibration of the initial parameter information of the inspection point; installing a track system according to the inspection environment map model, setting an inspection mode, and mounting and operating an inspection robot on the track system based on the inspection mode; and calibrating the track mileage to obtain the calibrated track mileage, and positioning the inspection robot to the position of the robot by using the positioning tag reader and the multi-circle absolute value encoder based on the calibrated track mileage so as to monitor whether the equipment to be inspected has a fault or not.

The specification discloses an image recognition-based robot charging method, system and electronic equipment, which has the advantages of low cost, high precision, wide recognition range, etc. The method comprises: acquiring a work scene image by using a monocular camera on the robot, and extracting a charging pile image from the work scene image; performing image recognition on the charging pile image to obtain position information of a feature icon on the charging pile in the charging pile image; judging a positional relationship between the robot and the charging pile according to the position information; performing path planning according to the positional relationship, generating charging path parameters, and controlling the robot to move to the charging pile for charging based on the charging path parameters. The system comprises: a charging pile image extraction module, a feature icon positioning module, a robot positioning module, and a path planning control module. The processor in the electronic equipment implements the method when executing a program.

The invention discloses a multi-robot position measurement method and system based on tracking and scanning, and the method comprises the steps: firstly, fixing a calibrated three-dimensional target ball on a tail end flange of a robot, moving the robot for multiple times, and carrying out the tracking and scanning through a handheld scanner, thereby obtaining a three-dimensional point cloud of the surface of the target ball; recording a flange tail end attitude matrix of the robot to complete data acquisition; then, calculating the center of a target ball by adopting a least square ball fitting method, and calculating a mean square error of target ball fitting according to calibration data of the target ball to establish a target weight; and finally, establishing a transfer equation and a joint optimization objective function according to a robot coordinate system conversion relation, and calculating to obtain a position matrix between the robots to complete measurement. The method can adapt to a multi-robot system, is not limited by the number and types of the robots, can collect data of all the robots at the same time, is good in flexibility and universality, adopts a joint optimization solution mode based on the target weight, and has good stability and accuracy.

The invention discloses an anti-impact compliance control method, device and system for a robot tail end and a storage medium. The force information of the robot tail end is estimated based on the position, speed and joint motor torque information of a robot; and the abrupt change torque of the end effector is compensated through the trained network system, and the anti-impact performance and the contact flexibility performance of the robot end effector are improved.

The invention relates to a two-dimensional target and three-dimensional point cloud registration method for manipulator positioning, and the method comprises the following steps: S01, collecting RGB-D data streams of a to-be-massaged part of a human body through a depth camera, reasoning an RGB image through a lightweight deep learning model, and outputting a bounding box coordinate of the to-be-massaged part and a pixel-level segmentation mask; s02, building a data channel based on a camera SDK, converting depth information into three-dimensional coordinates, endowing the three-dimensional coordinates with colors, and combining segmentation mask filtering point cloud, neighbor index and density filtering algorithm optimization to obtain pure point cloud; s03, establishing image coordinate correspondence according to camera calibration parameters, and registering the acupuncture point two-dimensional coordinates and the point cloud projection coordinates to obtain an acupuncture point three-dimensional coordinate set; and S04, comparing the three-dimensional coordinates of the acupuncture points with the reference coordinates to calculate errors, judging whether the registration is qualified or not, if not, re-executing the previous steps, and meanwhile, downsampling pure point clouds, so that the aim of improving the registration precision and efficiency and ensuring the precise operation of the massage robot is achieved.

The application relates to the intelligent robot technology in the field of artificial intelligence, and discloses a robot position correction method and related equipment, the method comprising: acquiring a first actual distance of a robot and a reference line in a target direction and a first heading angle of the robot relative to the reference line, the reference line being a boundary line of a target object, the target direction being a vertical direction of the reference line, the first heading angle being an included angle between a moving direction of the robot and the reference line, and the target object being an object related to a task performed by the robot; and controlling the robot to move according to an expected distance of the robot and the reference line in the target direction, the first actual distance and the first heading angle, so that a second actual distance of the moved robot and the reference line in the target direction is the expected distance. The relative positioning technology is used with the reference line to realize the correction of the robot position, and an automatic position correction scheme of the robot in the moving process is provided.

The invention discloses a robot positioning path dynamic planning method adaptive to non-uniformly distributed strain gauges, and belongs to the technical field of robot path planning, and the method comprises the steps: carrying out the double-layer clustering of the non-uniformly distributed strain gauges in a to-be-measured environment based on the positions and surface normal vectors of the strain gauges, and adding a virtual strain gauge in each inner-layer cluster; taking the virtual strain gauge as a positioning target, and generating an initial planning path for positioning the virtual strain gauge based on the GTSP; according to the initial planning path, virtual strain gauge images are sequentially collected through a strain gauge robot, and part of strain gauges in the virtual strain gauge images are positioned; and generating a planned path of the strain gauge robot based on the positioning results of part of the strain gauges, and dynamically adjusting the planned path until all the strain gauges are positioned. According to the method, the positioning effect of the non-uniform strain gauges is remarkably improved, the robustness is high, the automation degree is high, and the method can be adapted to positioning of various strain gauge distribution scenes.

This invention relates to an automated splicing arc welding production device. It employs a seven-axis transport robot positioned below an automated intelligent transport truss along a preset axis. Below the automated intelligent transport truss, and on one side of the seven-axis transport robot, several positioning trolleys are positioned along the preset axis. Below the automated intelligent transport truss, and on one side of the positioning trolleys' travel path, an assembly fixture is positioned. A welding robot is positioned on one side of the assembly fixture. The main control system controls the positioning trolleys to transport materials to the assembly fixture, where the seven-axis transport robot assembles the materials. The welding robot welds the assembled materials. The automated intelligent transport truss removes the welded materials from the production line. This device solves the technical problems of on-site chaos, frequent errors, low production efficiency, and high manual labor intensity.

The embodiment of the application provides a kind of multi-robot cooperative positioning method and device, equipment and storage medium, belong to robot positioning technical field.The method comprises: obtaining autonomous positioning information;Scan external marker, obtain observation data, and obtain the current position information of external marker;Wherein, external marker includes at least one of the following: second robot, road sign, landmark;According to observation data, current position information and autonomous positioning information, pose estimation is carried out to obtain update positioning information and the positioning estimation information of external marker;Update positioning information and positioning estimation information are sent to central server, to make central server obtain the positioning estimation information of at least one second robot to first robot to obtain positioning reference information, and according to positioning reference information and update positioning information, fusion calculation is carried out to obtain target positioning information;Receive target positioning information from central server.The embodiment of the application can improve the positioning accuracy of robot.

Systems and a method for predicting a motion trajectory of a robot moving between a given pair of robotic locations. Training data of motion trajectories of the robot are received for a plurality of robotic location pairs. The training data are processed so as to obtain x tuples and y tuples for machine learning purposes; wherein the x tuples describe the robotic location pair and the y tuples describe one or more intermediate robotic locations at specific time stamps during the motion of the robot between the locations of the location pair. From the processed data, a function is learned for mapping the x tuples into the y tuples so as to generate a motion prediction module for the robot. For a given robotic location pair, the robotic motion between the given pair is predicted by obtaining the corresponding intermediate locations resulting from the motion prediction module.

The invention discloses a robot position identification method and system based on a laser radar multi-scale reverse view, and the method solves the problems that in a classical laser radar position identification method, point clouds are disordered and sparse, and the utilization rate of sensor information is not high through the construction of a multi-scale reverse view preprocessing module. A novel Mama-Transform feature encoder network is established, and the problems that in a traditional position recognition algorithm, a feature encoding model structure is relatively simple, and the global feature characterization capacity is poor in the feature extraction process are solved; a global feature fusion module is designed, and the problem that the robustness of an existing laser radar position recognition method is rapidly reduced in 180-degree reverse challenging scenes such as turning around and bidirectional driving is solved. Through the improvement of the technical scheme, the robot position recognition precision is greatly improved.

The application provides a large scene graph switching method, system and device and a storage medium, and the method comprises the following steps: S1, constructing a point cloud map and a graph database of a large scene; S2, robot positioning according to the graph map and real-time switching of the graph. The application firstly cuts the high-precision point cloud map of the complete large scene according to the graph, which is used for constructing the graph database of the complete large scene; then dynamically loads the graph around the current position of the robot according to the graph database, which is used for composing the graph map of the local large scene, and is used for real-time calculation of the position of the current robot in the large scene; and according to the current robot position and the predicted action path, it is decided which graphs in the graph database are switched to at present, and the graph map of the local large scene is updated in real time; the robot can realize fast and real-time graph switching in the super large scene without feeling, and accurate 3D space positioning can be realized on the hardware device with limited computing power.

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.

An autonomous mobile robot includes a drive system supporting the robot above a surface, a sensor system configured to generate a signal indicative of a position of the robot on the surface, and a controller operably connected to the drive system and the sensor system. The drive system is operable to navigate the robot around the surface. The controller is configured to execute the instructions to operate, including establishing a behavioral control zone on the surface, in response to establishing the behavioral control zone on the surface, controlling the drive system to manipulate the robot to a location of the behavioral control zone on the surface, and manipulating the robot around the surface using the drive system, and initiate a behavior in response to determining that the robot approaches the behavior control region based on the signal indicative of the position of the robot.

The invention discloses a magnetic micro-robot dynamic path planning method based on a composite artificial potential field, and relates to the technical field of micro-nano operation, and the method comprises the steps: inputting map information to generate an initial path, optimizing path points in each path segment, and outputting a continuous and smooth global path; based on the position relation between the robot position and the global path, composite path adsorption attraction is applied; when the algorithm falls into a local minimum, constructing a disturbance sampling area based on the position of the robot, a target point and a global path, randomly generating a temporary gravitational point in the area, applying auxiliary disturbance gravitational force, and guiding the robot to jump out of a trap area; and the target point gravitation, the obstacle repulsive force, the composite path adsorption gravitation and the auxiliary disturbance gravitation are synthesized into control guiding force, and the robot is driven to move in the set target direction. The method integrates path guidance, dynamic obstacle avoidance and local optimization capabilities, and is suitable for path planning tasks of various intelligent moving bodies in a complex environment.

The invention discloses a continuum robot position tracking and joint limiting avoidance method, and belongs to the field of robot control. According to the method, a current path is obtained through forward kinematics modeling, joint limiting constraint and ideal path generation are combined, a nonlinear programming problem with the maximum path deviation and the minimum path deviation as the target is constructed, and joint increment is iteratively solved to achieve end tracking and overall path fitting. According to the method, the problem that inverse kinematics is difficult to solve is avoided, joint overrun is explicitly avoided, and the method is suitable for high-precision and high-reliability control in a narrow space and an obstacle environment.

This invention relates to a method for predicting robot position errors and their intervals. The steps include: acquiring the joint angle vectors of an industrial robot during operation and calculating the difference between the theoretical and actual positions to construct a dataset containing the joint angle vectors and position errors; inputting the dataset containing the joint angle vectors and position errors into a neural network-based prediction model; predicting the position error interval by calculating the predicted interval coverage probability and the average predicted interval width, while ensuring the predicted interval coverage probability meets the standard and minimizing the average predicted interval width; generating relative weights for the predicted interval boundaries by defining learnable parameters and using mean squared error loss to regress the predicted values ​​to predict the position error; and outputting the position error value and its interval prediction result from the prediction model. Compared with existing technologies, this invention can not only predict position errors but also predict the error range, improving the applicability and effectiveness of position error prediction.

The invention relates to the technical field of robot position measurement, in particular to a robot positioning method, device and equipment and a storage medium, and the method comprises the steps: carrying out the data fusion of robot satellite positioning data and robot motion data, and obtaining robot positioning information; performing feature detection on the binocular environment image to obtain target environment feature information; generating a feature map based on the robot positioning information and the target environment feature information; and determining the target position of the robot based on the robot satellite positioning data, the robot motion data, the robot positioning information, the binocular environment image, the target environment feature information and the feature map. According to the invention, the robustness and accuracy of the robot positioning process can be improved.

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 utility model relates to the technical field of automatic production equipment, in particular to a height-adjustable feeding and discharging mechanical arm with a sliding table. In order to solve the problems that in the prior art, the position of a feeding and discharging robot is fixed, the feeding and discharging robot cannot move along with an assembly line, the height is fixed, and the compatibility of machined products is poor, an innovative solution is provided. The mechanical arm comprises a sliding table, a heightening table and a mechanical arm body, through the structural design of the sliding table and a sliding rail, the mechanical arm body can move left and right on the sliding rail, and the mechanical arm body can move along with materials on an assembly line to conduct feeding and discharging operation. And meanwhile, the adjustable heightening table is arranged on the sliding seat and connected with the mechanical arm in a nut connection mode, so that the height of the mechanical arm can be rapidly adjusted according to the height of the machined workpiece, and the compatibility of the mechanical arm to different machined products is improved.

This invention discloses a robot pathfinding method, pathfinding device, equipment, and computer-readable storage medium. The method includes obtaining the robot's position and the charging dock's position in a grid map; obtaining the shortest path from the robot's position to the charging dock's position; determining candidate transfer stations from the robot's position to the charging dock's position if the shortest path passes through obstacles; determining a first target transfer station corresponding to the robot's position and a second target transfer station corresponding to the charging dock's position from the candidate transfer stations; obtaining all candidate transfer paths from the first target transfer station to the second target transfer station; selecting the shortest candidate path that does not pass through obstacles as the target transfer path; and determining the target path from the robot's position to the charging dock's position based on the path from the robot's position to the first target transfer station, the target transfer path, and the path from the second target transfer station to the charging dock's position. This invention has the advantages of low computational load and high execution speed.

1. Name of the product in this design: Graphical User Interface for Controlling the Operating Program of Electronic Equipment. 2. Intended use of this design: for use in an electronic device. 3. The key design features of this product are the content and layout of the graphical user interface on the screen. 4. The image or photograph that best illustrates the design's key features: the front view. 5. Purpose of the graphical user interface: This graphical user interface is used to set robot positions, generate robot programs, and access robot function parameter settings. The text icons in the middle, "Safety Point," "Start Point," "Arc Start Point," "Arc Extinction Point," and "End Point," along with the five corresponding indicator lights on the right, use different colors of the indicator lights to show the specific steps and nodes in the weld seam program settings. Green indicates points that have been taught, yellow indicates points that are currently being taught, and red indicates points that have not been taught. Click the circular green "Teach" button on the page or press the "Teach" physical button to complete the teaching of the current point. After a successful demonstration, the point will turn green, and the next point will automatically turn yellow. Click the "Dry Run" or "Weld" button to generate and run the robot program. Clicking on other buttons on the page will take you to the corresponding function parameter settings.

The invention discloses a compliance control method in an amphibious environment and a flexible robot, and relates to the field of amphibious robot control, the bottom of each leg of the amphibious robot is provided with a corresponding elastic element, and the amphibious robot designs a multi-sensor integration algorithm switching working mode based on an inertial measurement unit IMU and a depth gauge. And corresponding passive compliance control algorithms are selected in different working modes to guide the motion posture of the robot, and meanwhile, the poses of motors on the legs are controlled based on the output of the feed-forward fuzzy PID controller, so that the position of the robot is controlled by controlling the rotation angles of the motors. The invention provides a compliance control method in an amphibious environment and a flexible robot, which are suitable for an amphibious robot of which the bottom of each leg is provided with a corresponding elastic element, and the adaptability and reactivity in a complex environment are enhanced by designing a corresponding kinetic model and a control strategy.

The invention discloses a robot positioning confidence coefficient determination method and device, equipment and a storage medium. The method comprises the following steps: based on a normal distribution transformation positioning algorithm, a prior point cloud map and an initial pose of a robot, determining a European style fitness score between the prior point cloud map and a target frame laser point cloud; in response to the European style fitness score meeting a preset convergence condition, determining the European style fitness score in a convergence state as a target European style fitness score, and obtaining a target matching transformation probability value and a target matching parameter; based on the target matching transformation probability value and the target matching parameter, determining the positioning reliability of a normal distribution transformation positioning algorithm for positioning the target frame laser point cloud; and based on the target European style fitness score and the positioning reliability, determining candidate positioning confidence, and normalizing the candidate positioning confidence to obtain the target positioning confidence. According to the invention, the accuracy of robot positioning confidence determination can be improved, and the reliability of robot positioning can be accurately reflected.