373 results about "Robot position" patented technology

The invention discloses an automatic goods warehousing method and system for intelligent warehousing, and belongs to the technical field of intelligent warehousing. According to the method, dynamic event information such as cargo elevator fault signals and robot position conflict detection data is obtained through a real-time data interface, a dynamic path self-adaptive scheduling mechanism is constructed based on a path planning algorithm, and a standby path set is preset; when a dynamic event is detected, the edge calculation unit is triggered to complete a standby path calculation strategy within a system preset time threshold value, and finally the storage robot is controlled to execute storage work according to a planned path. The system comprises a data sensing module, a path planning module, an edge calculation unit and an execution control module, and the modules cooperate to realize real-time path optimization under a dynamic event. According to the method, the problems of insufficient dynamic scene adaptability and low equipment cooperation efficiency in traditional storage are effectively solved, the storage efficiency is improved, and the energy consumption is reduced.

The invention provides a robot positioning prediction method and device, a medium and equipment, and relates to the field of industrial robot motion control. According to the method, on one hand, a physical-data double-branch collaborative network is designed, meanwhile, a DH parameter method is used for predicting and obtaining a theoretical position coordinate of a target robot, an improved Transform network is used for predicting and obtaining a coordinate compensation value of the target robot, so that a theoretical value and the compensation value are decoupled, and the limitation of single model establishment is avoided; and then, the two are fused, and high-precision end point location prediction for the target robot is realized by combining priori knowledge of robot kinematics and nonlinear expression ability of deep learning. And on the other hand, a spatial physical information mixed loss function is provided, and a spatial topological structure output by the DH model is used to guide the distribution of predicted values of the whole position prediction model, so that the geometric rationality of target robot end point location prediction is improved.

The invention discloses a photovoltaic cleaning robot operation scheduling method and system based on environment prediction, and belongs to the technical field of photovoltaic power station intelligent operation and maintenance and robots, and the method comprises the steps: obtaining weather forecast data, photovoltaic panel real-time dust accumulation data and historical power generation efficiency attenuation data, and generating environment prediction parameters; generating a dynamic weight value based on the environment prediction parameters and a preset power generation loss threshold value, and judging the sweeping emergency degree of each photovoltaic panel area; distributing an operation priority according to the cleaning emergency degree, and generating an initial cleaning task sequence; and a multi-robot cooperative path planning result is generated by combining the photovoltaic power station topological structure and the real-time position data of the robots. According to the method, the environment prediction technology and the dynamic scheduling strategy are combined, the cleaning task can be adaptively adjusted according to weather changes and dust accumulation conditions, the robot operation path is optimized, and the power generation efficiency of a photovoltaic power station and the utilization rate of robot resources are remarkably improved.

A robot system for picking randomly shaped and sized object from a continuously moving stream of objects in bulk, e.g. a 3D bulk, and placing the object singulated and aligned on an induction or directly on a sorter. A pick and place robot has a robotic actuator for moving a gripper with a controllable gripping configuration of its gripping members, e.g. four suction cups, to adapt the gripper for various objects. A control system processes a 3D image of objects upstream of a position of the pick and place robot, identifies separate objects in the 3D image, and selects which object to grip, based on parameters of the identified separate objects determined from the 3D image. Based on e.g. size and shape of the selected object to grip, the gripping configuration of the gripper is adjusted to match the surface of the object to grip for optimal gripping. The robotic actuator, e.g. a gantry type robotic actuator, is then controlled to move the gripper to a position for gripping the object, and afterwards move the gripper with the gripped object to a target position and with a target orientation to release grip of the object and thus place the object on an induction or directly on a sorter. An image after placing the object along with properties of the object determined from the 3D image can be used as input to a machine learning for online improving pick and place performance of the robot system, e.g. for online improving the algorithm for selection of which object to pick, and also for selection of the appropriate gripping configuration to match the object.

An adaptive variable-structure duct robot motion control method based on environmental sensing. A duct robot is a dual-swing-arm tracked mechanism, and onboard sensing devices include a depth camera, an IMU, a wheel speed sensor and a TOF module. The method comprises: a depth camera capturing an image of the interior of a duct to perform scenario recognition, segmenting planar and curved surfaces in the image on the basis of scenario recognition results, and extracting edge lines of the duct; using the edge lines to calculate the width of a straight duct, the curvature of a curved duct, the angle of a slope and the height of a step, in order to determine the passability of a 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 processing, and inputting the smoothed reference trajectory and swing arm angle sequence into an MPC motion controller; using data from the depth camera, an IMU and a wheel speed sensor to estimate the position and state of the robot by means of an ESKF algorithm, and inputting estimation results and a collision warning signal from a TOF module into the MPC motion controller in real time; and finally, outputting control signals for a locomotion electric motor and a swing arm electric motor. Thus, the adaptive variable-structure and autonomous motion of a robot in different scenarios is realized.

A cleaning system for cleaning an electronic device includes an enclosure and at least one robot positioned within the enclosure. Each robot includes a robotic arm and an end effector coupled to the robotic arm. The cleaning system includes at least one nozzle positioned within the enclosure and at least one dry ice blasting machine configured to eject dry ice particles from the at least one nozzle. The robot is configured to position the electronic device proximate to the at least one nozzle to clean the electronic device with the dry ice particles that are ejected from the at least one nozzle.

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.

The invention relates to the technical field of underwater robot control, in particular to an autonomous line patrol motion control method of an underwater cable detection robot, which comprises the following steps of: establishing a six-degree-of-freedom kinematics equation and a kinetic model of the robot, and collecting position information of the robot and a current heading angle of the robot; the target heading angle of the robot is calculated through an optimal deflection angle fusion algorithm, the current heading angle, collected by a sensor, of the robot is compared with the target heading angle, an error epsi is obtained, and the error epsi is added into a single-ring PID algorithm for adjustment; and controlling the thrust and direction of a propeller in the underwater cable detection robot according to a control signal tau (t) output by the single-loop PID algorithm and robot position information, judging whether a target heading angle of the underwater cable detection robot is consistent with a current heading angle, if so, completing autonomous line patrol, otherwise, continuing to correct, and if not, completing the detection of the underwater cable detection robot. The attitude control precision and the path navigation stability of the robot in the underwater environment are improved.

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.

The invention provides an intelligent robot path scheduling method and system for scenic spot tourists, and relates to the technical field of path scheduling, and the method comprises the steps: obtaining robot position and state information and tourist service request information, and building a scenic spot electronic map; constructing a robot service capability evaluation model; path planning and scoring are carried out, and an optimal service path is selected; selecting the most suitable target service robot; sending the optimal service path to the target robot and loading the optimal service path; the motion trail of the robot is monitored in real time, and the path is dynamically adjusted if necessary. According to the method, the scenic spot service efficiency and tourist experience are improved.

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 provides an electromagnetic driving system. In one embodiment, the electromagnetic drive system comprises: a) one or more magnetic robots located within a workspace; b) three independent mechanical arms, wherein each independent mechanical arm comprises a movable electromagnetic coil; c) a positioning system for tracking the one or more magnetic robots; the three independent mechanical arms are controlled through multi-objective optimization to ensure a coil configuration space capable of providing a magnetic field for manipulating the one or more magnetic robots in the working space.

The invention provides a robot autonomous positioning system and method based on a three-dimensional model technology, relates to the field of intelligent autonomous positioning, and realizes rough positioning of a robot by constructing a global map feature descriptor search library and a block index and combining image information. And the point cloud feature information is accurately matched in the corresponding blocks to calculate the position and posture of the robot. According to the method, feature coding is carried out on robot image information, retrieval correspondence is carried out on the robot image information and pre-constructed block indexes, and matching is carried out after related block indexes are extracted, so that the semantic matching degree is intelligently estimated and compared with a preset threshold value, and whether the robot image information is included into one of the block indexes which are roughly positioned globally or not is determined; therefore, the high accuracy of the preliminary positioning stage is ensured, the error accumulation in the subsequent steps is reduced, and the stability of the whole positioning process is enhanced.

The present invention discloses a master-slave control method and system for a master-slave heterogeneous teleoperation system, including: an operator inputs the link parameters of the slave robot for forward kinematics and inverse kinematics analysis to obtain forward kinematics and inverse kinematics models; the operator modifies the master-slave mapping scale coefficient to achieve the movement of the slave robot with different efficiencies and accuracies; a variable-scale incremental master-slave mapping method is designed to realize the mapping from the position increment of the master robot to the position increment of the slave robot, and a BP neural network is designed to predict and compensate the master-slave following error, further reducing the master-slave following error. The present invention can not only realize the large-range movement of the slave robot in free space, but also ensure the movement positioning accuracy in the fine operation space, with strong versatility and convenient implementation.

The invention relates to a system for multi-robot collaborative operation, intelligent task allocation and path planning. The system comprises a task receiving module, a task decomposition module, an execution module, a path planning module and a path calculation module, the task receiving module is used for receiving task information and transmitting the task information to the task decomposition module; the task decomposition module is used for generating sub-task information according to the received task information and distributing the sub-task information to the corresponding robots through the task distribution module of the execution module; the execution module is used for distributing tasks according to the subtask difficulty, the duration and the current load of the robot; and the path planning module is used for sending planning path information and controlling collision-free operation based on the position state of the robot. Through a multi-module collaborative task intelligent allocation mechanism, dynamic obstacle avoidance path planning based on an artificial potential field method and a multi-end-point adaptive adjustment strategy, multi-robot operation load balancing, path collision-free and environment dynamic adaptation are realized, and the collaborative efficiency and safety are remarkably improved.

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 region segmentation and exploration estimation method and device based on geometric features, computer equipment and a storage medium. The method comprises the following steps: constructing a wall map; performing region segmentation on the wall map to obtain a region segmentation result; robot position information and direction information are obtained, and a visible area is obtained through calculation according to the position information and the direction information; calculating according to the visible area to obtain an exploration area point set; performing calculation according to the region segmentation result and the exploration region point set to obtain a region exploration rate; setting an exploration priority according to the regional exploration rate; formulating a path planning and exploration strategy; and guiding the robot to act in combination with the exploration priority, the path planning and the exploration strategy. The method has the remarkable technical effects of improving the navigation efficiency, reducing redundant exploration, enhancing the practicability and reliability of the navigation system and the like. The technical scheme can be applied to the field of medical treatment and logistics robots.

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 the technical field of medical auxiliary instruments, in particular to an arthroscopic surgery electromagnetic navigation robot which comprises an operating bed, a first robot and a second robot are arranged on one side of the operating bed, an electromagnetic generator assembly is installed on the operating bed, and a guide needle is detachably installed at the movable end of the first robot; an electromagnetic receiver is installed on the guide pin, and an ultrasonic imaging assembly is installed at the movable end of the second robot. According to the invention, the robot is used for replacing people for operation, and a part with a navigation function is arranged, so that the operation can be more accurately implemented and completed.

The invention belongs to the related technical field of robot positioning mapping, and discloses a robot positioning mapping method and device based on multi-sensor fusion, and the method comprises the steps: (1) employing a monocular camera, a laser radar and an IMU to perceive the surrounding environment of a robot, so as to obtain an image, a laser point cloud and acceleration information; (2) calculating the offset of the IMU, providing scale information for the monocular camera, and performing pre-integration on the measured value of the IMU to obtain an IMU pre-integration factor; (3) acquiring a laser odometer factor and a visual odometer factor; extracting a key frame at the same time; (4) establishing a bag-of-word model for the extracted visual key frame, and carrying out loopback detection on the visual key frame by adopting the bag-of-word model; and (5) adding an IMU pre-integration factor, a visual odometer factor, a laser odometer factor and a loopback factor as constraints of a factor graph, and optimizing the factor graph to obtain a pose to adjust the obtained point cloud map. The precision and the efficiency are guaranteed.

The invention provides a visual identification positioning method, device and equipment for a robot, and the method comprises the steps: collecting a plurality of frames of left and right target images through a stereo camera, carrying out the dual feature detection of the images, extracting point features and line features, and forming complementary feature information; matching optimization processing is carried out on the point-line features, and a high-quality feature matching result is obtained; key frame selection is carried out based on a point-line fusion feature matching result, and redundancy calculation is reduced; and carrying out three-dimensional reconstruction on point-line features in the key frame, and carrying out fusion optimization with inertial measurement unit data to obtain accurate robot position and attitude information. Through a point-line feature fusion mode, the limitation of purely depending on point features in a texture missing environment is effectively solved, the precision and robustness of robot vision positioning are remarkably improved, and the method is suitable for robot autonomous navigation in texture missing and rugged terrain environments.

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 invention discloses a multi-mode RGBD robot autonomous positioning method based on an optimal luminosity difference, and the method comprises the steps: carrying out the pixel-level alignment in a coincident view field based on a camera-laser radar joint calibration parameter, and generating an RGBD point; combining distance information and color information in an iterative nearest point to construct an objective function, matching the current point with a historical map point, and calculating to obtain a pose; adding the currently scanned laser point cloud into a historical map, carrying out color estimation on the point cloud which does not obtain RGB information, expanding the color detail expression of the map, and obtaining an optimized pose; and updating the scene RGBD map based on the optimized pose, and outputting the pose estimation result of the current frame to obtain the position of the current robot. According to the method, the depth information acquired by the laser radar and the color texture information acquired by the camera are fused, the environment features are extracted from two dimensions, and the limitation of the low-harness laser radar under the conditions of low point cloud density and insufficient environment detail expression is effectively made up.

The invention discloses a routing inspection path generation method and device suitable for a transformer substation, terminal equipment and a storage medium, and belongs to the technical field of transformer substation routing inspection.The routing inspection path generation method suitable for the transformer substation comprises the steps that site data and robot routing inspection data are input into a path planning model; according to the method and the system, a model is established, so that the model can extract site features and obstacle distribution features from site data and extract robot space occupation features and robot position features from robot inspection data, when the inspection path is generated, data of moving obstacles are considered, the moving obstacles can be effectively avoided, and the inspection efficiency is improved; according to the method, when the robot inspection path is obtained, the site features and the features of all the obstacles are considered, the features of the robot are also considered, and the problem that in the prior art, it is difficult for the robot to smoothly complete the inspection task in the complex and changeable environment can be solved.

Provided is a robot including: a body rotatable about a first shaft; a first drive wheel and a second drive wheel provided in the body to be rotatable about a second shaft that is perpendicular to the first shaft; at least one distance sensor provided on the second shaft; and a processor. The processor may acquire first distance information through the at least one distance sensor at each of a plurality of different points at which the body is located as the body moves; acquire second distance information through the at least one distance sensor in each of a plurality of different directions in which the body is directed as the body rotates; and acquire, based on the first distance information and the second distance information, acquire information about a location point of the robot on a map corresponding to a space in which the robot is located.