175 results about "3d sensor" patented technology

A method for managing an agricultural vehicle during harvesting process in a plantation of fruit trees, such as an orange orchard, the vehicle being shaped as a portal capable of moving over a crop row and provided with a couple of rotors (R) arranged to work simultaneously on both opposite sides of each plant of the crop row, the method including process of recognition of the trunks of the trees of a plantation to be worked by means of a first 3D sensor (3DS) system interfaced with processing means (CPU) of an agricultural vehicle (V), wherein the first 3D sensor (3DS) system includes a couple of 3D sensors arranged in a low portion of the agricultural vehicle at opposite sides of the vehicle oriented such that to converge in common point (P) circa on a vehicle center line axis (VC) in front of the vehicle, the process including fitting of pseudo-ellipsoids in a horizontal slice of a merged point cloud generated by the two 3D sensors, in order to identify trunks of the crop row.

Geo-localization is the process by which an entity, such as an autonomous vehicle, can determine its precise location. In an example, a vehicle may include sensors, such as 4D radar sensors, that can capture a point cloud representing an environment within which the vehicle is positioned. An efficient representation of the point cloud is generated, which may be preceded by filtering the point cloud by removing points associated with transient elements. The efficient representation may be based on applying dimensionality reduction techniques to the point cloud or the filtered point cloud. The efficient representation may be compared with previously-generated representations which include geo-location, and were generated by the same dimensionality reduction techniques. Based on determining a match, the geo-location associated with the matched previously-generated representation may be assigned as a current geo-location of the vehicle.

In accordance with one aspect of the inventive concepts, provided is an autonomous mobile robot (AMR), comprising: at least one processor in communication with at least one computer memory device; at least one 3D sensor configured to collect 3D sensor data of an object; and a fixed scale image processing module configured to receive the 3D point cloud data; transform the 3D point cloud data into at least one fixed scale (FS) image; detect, identify, and localize the object in image space of the at least one FS image; select a plugin associated with an object type of the object; and apply the plugin for 6D (degrees of freedom) pose estimation of the object in real-world space to localize the object. In various embodiments, the object can be any type of forkable object, but in other embodiments the object need not be a forkable object.

Autonomous control system of a weeding tool connected to an agricultural vehicle (AV), wherein the weeding tool is able to assume a weeding condition and a retracted condition, wherein said weeding condition includes a distension of the tool according to a direction perpendicular to a longitudinal development (L) of the vehicle; the system comprising a 3D sensor (3DS) associated with a front part of the agricultural vehicle to acquire a pointcloud corresponding to a scenario in front of the vehicle (AV), and processing means (ECU) configured cyclically to generate a map of poles and / or trunks detected by means of said pointcloud, and command a weeding condition of the implement when the distance between the implement and a pole and / or trunk is greater than a predetermined threshold and command a retraction condition of the implement when said distance is less than or equal at said predetermined threshold.

The invention relates to the field of optical measurement devices, in particular to displacement sensors, 3D sensors for measuring the position and / or shape or thickness of a measurement object. Measurement light is projected onto a measurement object after5 filtering by a Fabry-Pérot filter such that at each point in a measurement plane, the filtered measurement light has a locally unique wavelength or combination of wavelengths in at least one direction in the measurement plane. Measurement light reflected from the surface of the measurement object is also filtered by a Fabry-Pérot filter in order to filter out measurement light not reflected from the intersection of the measurement object with0 the measurement plane. To be published with

The present invention relates to a system for monitoring a surgical luminaire assembly comprising at least one surgical luminaire, with a monitoring unit. It is provided here that the system comprises a 3D sensor which three-dimensionally detects the surgical luminaire assembly and / or an operating area arranged below the surgical luminaire assembly, wherein the data of the 3D sensor are evaluated by the monitoring unit with respect to the surgical luminaire assembly.

The invention discloses a steam turbine blade surface image acquisition method and system based on 3D visual path planning, the system comprises an industrial robot, a product tooling platform, a surface data acquisition unit and a geometrical optical unit, the surface data acquisition unit comprises a 3D sensor and a 2D industrial camera, the geometrical optical unit is formed by combining a plurality of optical light sources, and the 3D sensor is connected with the 2D industrial camera. The blade is illuminated at different angles and under different illumination conditions, details and features of the surface of the blade can be highlighted, and the contrast ratio and definition of the image are improved. The method can be widely applied to industrial detection and maintenance, the position and angle of the acquisition equipment can be dynamically adjusted by constructing the 3D model of the blade in real time and intelligently planning an acquisition path algorithm, and a data acquisition system is guided to realize comprehensive and accurate image acquisition on the surface of the blade through accurate path planning and multi-view fusion.

Computer-implemented method 100 for navigating a robot in an environment includes: Step 402, constructing a point cloud map representing the environment, based on 3D sensor data. Step 404, determining

An example computing device includes: a three-dimensional (3D) sensor configured to capture point cloud data from a field of view; an auxiliary sensor configured to capture a reference depth measurement corresponding to a surface within the field of view; a processor interconnected with the 3D sensor and the auxiliary sensor, the processor configured to: control the 3D sensor and the auxiliary sensor to capture the point cloud data and the reference depth measurement; select a region of the point could data including a position of the reference depth measurement; determine a representative depth value of the region of the point cloud data to compare to the reference depth measurement; determine whether the representative depth value is within a similarity threshold to the reference depth measurement; and determine, based on whether the representative depth value is within the similarity threshold to the reference depth measurement, whether to use the point cloud data for a dimensioning operation.

An apparatus may be configured to perform a perception task based on features fused with height information. The apparatus configured may generate 3D sensor features from data from one or more sensors, generate a plurality of height maps from the 3D sensor features at a plurality of times, generate a height gradient map from the plurality of height maps, fuse the 3D sensor features and the height gradient map to generate height informed fused features, and perform the perception task using the height informed fused features.

To provide a learning data acquisition device and a learning data acquisition method capable of suppressing a deterioration in the prediction accuracy of a model and reducing time and effort required to acquire learning data.SOLUTION: In a welding system 1, an AI model generation device 2 being a learning data acquisition device includes an uncorrected image data storage part 211 for storing image data of a 3D image acquired by photographing a welding place by a 3D sensor 36, and a processor 22 for specifying a point at which a value of a Z coordinate satisfies a prescribed condition in the image data stored in the uncorrected image data storage part 211 as a data loss point, correcting the Z coordinate of the data loss point in the image data stored in the uncorrected image data storage part 211, and acquiring the corrected image data as image data to be used for machine learning.SELECTED DRAWING: Figure 1

The invention belongs to the technical field of tower building machine equipment, and particularly relates to a bridge tower concrete rotational symmetry vibrating device integrated on a tower building machine. Comprising a supporting device arranged on an inner supporting column and an outer supporting column of the tower building machine, a rotational symmetry mechanism arranged on the supporting device, a vibrating device arranged on the rotational symmetry mechanism, a sensing system and a control system. The sensing system adopts a 3D sensor and a distributed optical fiber vibration monitoring system (DAS) to realize dynamic monitoring of the vibrating process, the 3D sensor is arranged below the rotational symmetry mechanism, acquires point cloud data of the contour of the reinforcing mesh and provides original data for identifying the center of a hole of the reinforcing mesh, the DAS acquires vibration information of concrete when the vibrating mechanism works, and the vibration information of the concrete is acquired by the DAS. And data is provided for judging the vibration source position and the vibration quality of concrete in each area. Intelligent vibration of bridge tower concrete materials can be automatically completed, the current situation of manual construction vibration at present is broken through, the construction efficiency and the construction quality are improved, and a new scheme is provided for bridge tower concrete construction vibration.

The invention provides a pallet identification method based on 3D point cloud for an intelligent transfer robot. The pallet identification method comprises the following steps: S1, intercepting a target area from the 3D point cloud acquired by the intelligent transfer robot; s2, filtering noisy points through statistical filtering to obtain filtered point clouds; s3, identifying the ground from the filtered point clouds, removing the ground, and segmenting pallet point clouds according to the Euclidean distance; s4, projecting the pallet point cloud into the front view to obtain a 2D image; s5, constructing a front view template of the pallet and searching similar contours in the 2D image to obtain a pallet area; s6, the pallet 3D point cloud and the middle supporting leg 3D point cloud are reversely deduced; s7, extracting a front point cloud close to the front surface of the pallet; s8, obtaining a pallet placement angle according to the front point cloud, and obtaining the center position of the front surface of the pallet according to the 3D point cloud of the middle supporting leg; and S9, outputting, and completing pallet identification. The method is suitable for various 3D sensors, is high in universality and expansibility, does not depend on training and reasoning of a neural network, can be rapidly deployed, and is low in requirement for calculation performance.

A system and method determine the position of an elevator car movably arranged in an elevator shaft of an elevator system. The system has a 3D sensor, an evaluation unit communicating with the sensor, and a marking element. The sensor has a plurality of sensor cells and the evaluation unit uses measurement data received from the sensor to determine a distance from each sensor cell to a part of a detected object. The sensor is arranged such that in a normal mode of the system it detects the marking element as the object. The evaluation unit determines the position of the elevator car in the elevator shaft based on distances from sensor cells to the detected part of the object, continuously performs a test as to whether the sensor detects the marking element and brings the system into an error mode as soon as the test is negative.

Method and apparatus for a 3D sensor having die Hall element clusters located on first and second die. In an embodiment, a sensor IC package includes a first die having first, second, and third Hall clusters having different axes of magnetic field sensitivity and a second die having a fourth Hall cluster having sensitivity in the first and third axes of sensitivity. The sensor provides 3D field sensing for stroke, end of shaft and side shaft sensing applications.

A method and a system are disclosed for maintaining accuracy of a photogrammetry system comprising a stereo pair of cameras and characterized by calibration parameters determined at initialization, the system for tracking one of a touch probe and a 3D sensor, the method comprising in use, continuously detecting a presence of a reduced number of 3D target points comprising at least one pair of 3D target points selected in a group comprising at least two 3D target points; measuring image position data associated with the at least one pair of 3D target points of the reduced number of 3D target points; computing at least one updated calibration parameter using the measured image position data and corresponding reference distance data associated with the at least one pair of 3D target points of the reduced number of 3D target points; and updating at least one calibration parameter of the photogrammetry system.

The present application belongs to the technical field of construction engineering equipment, and specifically relates to a ring area steel mesh hole positioning test device and method based on 3D vision. Mainly includes the following contents: the 3D sensor is driven to scan the steel mesh through a rotating mechanism, and a steel mesh point cloud image is obtained; the steel mesh image is subjected to binaryzation processing, facilitating subsequent image analysis; the steel mesh image is skeletonized by using a 3D refinement algorithm, and a steel mesh skeleton is extracted; the neighborhood integral algorithm is used to find a steel intersection point set; the least square sphere fitting algorithm is used to fit and position a steel binding point; and the Varignon parallelogram method is used to position a steel mesh center hole. The method reduces the consumption of manpower, improves the construction efficiency, and helps to realize the automation and intelligentization of steel mesh area concrete construction.

The invention relates to a displacement sensor, for example as used in 3D sensors for measuring the three-dimensional shape of an object. A diffraction grating is used to reduce the angle of incidence of measurement light on a light sensor, such as an image sensor, thereby improving the performance of the light sensor. The displacement sensors of the present invention include sensors based on triangulation and coaxial sensors.

This invention relates to a measurement device that acquires measurement data obtained by measuring maintenance work by a worker by using a 3D sensor installed in a space in which maintenance work for a semiconductor manufacturing device is performed. The measurement device includes: an object identification unit 223 that identifies an object included in a raw data image acquired from a 3D sensor; a coordinate conversion unit 224 that acquires the position in space of the identified identification object; a work determination unit 225 that determines a work process being performed by a worker, on the basis of the movement of one or more identification objects; a region setting unit 226 that sets, in the raw data image, a region that can be output or cannot be output according to the work process; and a data limiting unit 227 that generates limited data in which a region of the raw data image that the region setting unit has set as a region that cannot be output is made invisible.

This invention belongs to the field of physical testing, specifically relating to an automated detection system for surface defects on a 3D sensor protective film. The system includes an acoustic-thermal excitation device, a thermal imaging sensing unit, an optical coherence tomography (OCT) scanning device, and a data processing and analysis terminal. The acoustic-thermal excitation device emits a focused ultrasonic beam onto the protective film surface to generate an acoustic-thermal effect; the thermal imaging sensing unit captures the spatiotemporal attenuation characteristics of the surface temperature field and generates a two-dimensional thermal diffusion feature map; the OCT scanning device adaptively acquires a three-dimensional structural cross-sectional image of the protective film based on the hotspot location; the data processing and analysis terminal performs spatial alignment and pixel-level fusion of multimodal data, and uses a deep neural network to identify defects. Through the above technical solution, this invention achieves non-contact, non-destructive, high-precision detection, balancing detection efficiency and accuracy. It can accurately identify deep, minute defects under complex coatings and predict the impact of defects on optical performance.

A 2D area array camera-line laser 3D sensor joint calibration method, comprising: establishing a 3D coordinate system of the line laser 3D sensor, and obtaining 3D coordinates of a light bar point on the 2D area array camera; placing a target at a common measurement position, and allowing the 2D area array camera to acquire images of intersection lines of three sets of laser plane and cylinders and the image coordinates of three sets of laser light bars respectively; calculating 3D coordinates of the light bar point in a 2D area array camera coordinate system, and calculating three ellipse center position coordinates; directly acquiring 3D coordinates of three sets of laser light bars in the 3D sensor coordinate system from the line laser 3D sensor, and calculating three ellipse center position coordinates; and calculating a conversion distance between two coordinate systems.

A method and system for registering a 3D sensor with an autonomous manipulator is provided. The 3D sensor has a field of view and a sensor coordinate system. The autonomous manipulator is a vision-guided manipulator having a work envelope and a manipulator coordinate system. The method includes moving a registration target relative to the sensor in the field of view of the sensor in the work envelope to obtain a plurality of depth maps or images of the target. The depth maps or images are processed to obtain a plurality of extrinsic registration parameters between the manipulator and the sensor.

The invention discloses a fan control system based on multi-module fusion, and relates to the technical field of fan control, in which a processor determines the feature center of a person and the feature center of each obstacle by using an image collected by a camera and an identification model; determining a first position of the person and each obstacle by using the point cloud segmentation model and the distance and angle between each position point and the 3D sensor; determining a failure judgment result; if not, determining an environment map and a target coordinate based on the feature centers of the person and each obstacle and the first position; if so, determining a second position of the person and each obstacle and determining an environment map and a target coordinate by using the point cloud segmentation model and the distance and angle between each position point and the ultrasonic sensor; and determining a planned path of the fan from the original point to the target coordinate by using a path planning algorithm and an environment map, controlling the moving module to move to the target coordinate, and blowing air to the person by the fan at the target coordinate. And flexible and efficient work of the fan is realized.

The present invention provides a pallet recognition and positioning method and system based on a 3D sensor. The steps of the recognition method include: S1 determining the parameters of each end face of the target pallet for recognition and establishing a feature template; S2 establishing a target point cloud based on the sensing data collected by the 3D sensor, and preprocessing the target point cloud. After filtering the ground point cloud, the point clouds of the same end face of the target pallet are merged to obtain a planar point cloud block; S3 converting the planar point cloud block into a 2D plane in the camera coordinate system through the external parameters of the 3D sensor; S4 establishing a coding map and placing the 2D plane therein, constructing a double-line sliding window with a preset feature recognition distance in the coding map and synchronously moving according to a preset step length to perform line segment fitting scanning on the points on the 2D plane encountered on the path. When it is determined that the current line lengths respectively fitted by the double-line sliding windows both conform to the feature template, the recognition result corresponding to the feature module is output. Thereby, a variety of 3D sensors are made universal to improve versatility, and at the same time, the requirements for computing performance are reduced.

The utility model discloses a steam turbine blade surface image acquisition system based on 3D visual path planning, which comprises an industrial robot unit, a product tooling platform unit, a surface data acquisition unit and a geometrical optics unit, and is characterized in that the surface data acquisition unit comprises a 3D sensor and a 2D industrial camera; the geometrical optical unit is formed by combining a plurality of optical light sources and illuminates the blade at different angles and under different illumination conditions, so that details and features of the surface of the blade can be highlighted, and the contrast ratio and definition of an image are improved. The system utilizes 3D visual path planning to guide the data acquisition unit to perform steam turbine blade surface image acquisition, can be widely applied to industrial detection and maintenance, can dynamically adjust the position and the angle of acquisition equipment, and can realize accurate path planning and multi-visual-angle fusion through accurate path planning and multi-visual-angle fusion. And the data acquisition system is guided to realize comprehensive and accurate image acquisition of the blade surface.

An embodiment sealer work automation system includes a robot configured to perform a brushing work of spreading a sealer applied to a joint by moving a brushing work tool to a work location of an under body, a three-dimensional (3D) sensor mounted on the robot and configured to photograph a work portion of the joint to acquire 3D data, a residual sealer remover configured to remove a residual sealer by applying a physical force to a brush of the brushing work tool contaminated after the brushing work, a robot path generator configured to generate a robot path for the brushing work by matching the 3D data received from the 3D sensor and design data for the brushing work of the joint, and a robot controller configured to control an overall operation of the robot and to control the brushing work of the robot based on the robot path.

An AI model generation device (2) is provided with: a captured image data storage unit (211) for storing image data of a 3D image obtained by capturing an image of a welding site by means of a 3D sensor (36); a processor (22) specifies a correction region on an XY coordinate plane of image data stored in a captured image data storage unit (211) on the basis of an input to a first input device (24) by a user, and corrects a Z coordinate of the correction region of the image data stored in the captured image data storage unit (211) to a value in a state in which there is no welding defect. And acquiring the corrected image data as image data used in machine learning.