CN112581451A - Warehouse coil position detection system and method based on laser radar - Google Patents
Warehouse coil position detection system and method based on laser radar Download PDFInfo
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Abstract
The invention provides a warehouse coil position detection system and method based on a laser radar, wherein a calibration plate is placed in a warehouse area, a single-line laser radar dynamically scans the calibration plate for calibration, external parameters of the single-line laser radar relative to a world coordinate system are obtained, and position and pose transformation is carried out to convert point cloud of the single-line laser radar coordinate system into the world coordinate system; the single-line laser radar dynamically scans the reservoir area, and performs pose transformation by combining the coordinates of the unmanned overhead crane to generate three-dimensional point cloud of the reservoir area; and obtaining the point cloud characteristics of the coil through point cloud processing and characteristic extraction, fitting the target point cloud, calculating the size information of the coil such as the length, the outer diameter and the like, and transmitting the coordinates of the coil under a world coordinate system to a library area management system. Experiments prove that the detection method of the embodiment can accurately generate the point cloud of the coil, accurately detect the shape and the position of the coil and has small error.
Description
Technical Field
The invention relates to the technical field of intelligent warehouse logistics, in particular to a warehouse coil position detection method and device based on a laser radar.
Background
The reservoir area is used as an important hub for logistics linkage and production rhythm control in the steel production process, and is the basis of factory unmanned and intelligent construction, and the crane is the most important execution unit of the reservoir area. Traditional steel rolling workshop reservoir district, hoist operation mainly relies on the manual work to accomplish, and workman intensity of labour is big, and reservoir district operating efficiency is low, and leads to personnel, equipment safety and data information to lose the scheduling problem easily. By researching and applying the unmanned crane and the intelligent warehouse management technology, the operation mode of the warehouse area is fundamentally changed, unmanned operation of the crane and intelligent dispatching of the warehouse area are realized, and the unmanned crane and intelligent dispatching method has important significance for improving production efficiency, reducing production cost and improving product quality.
At present, the position information of the coil of the reservoir area is acquired mainly by means of a three-dimensional reconstruction technology of laser point cloud on the reservoir area environment, and with the rapid development of a laser radar technology, the manufacturing and research cost is gradually reduced, so that the laser point cloud three-dimensional reconstruction technology is increasingly and widely applied to industrial fields. For example, in a first patent (a workshop steel coil laser radar three-dimensional positioning and measuring system, CN109782300A), a two-dimensional laser radar cross-section scanning is utilized to assist a laser range finder in positioning to perform spatial slice reconstruction, so that a task of performing three-dimensional reconstruction by using the two-dimensional laser radar is effectively completed, and target positioning and classification of steel coil point cloud are realized by combining gradient descent smoothing, a connected domain clustering method and a radial distortion correction algorithm, but the rail matching in an experiment is required, and the system is not suitable for intelligent transformation of an existing reservoir area; in the first literature (zhang, wang, chenko-based indoor scene three-dimensional reconstruction system design [ J ] electronic design engineering, 2019.) aiming at the problem of three-dimensional reconstruction of indoor scenes, a three-dimensional reconstruction system is designed by adopting a laser ranging method and combining technologies such as sensors, motor control and the like, the data of a laser radar, an inertia element and a speed-measuring code disc are fused through Kalman filtering, the position information of a robot is calculated, and a three-dimensional point cloud map of the indoor scene is obtained, but the problems of scanning accuracy and target identification are not involved, and characteristic extraction and target identification are required to be carried out on the basis of three-dimensional reconstruction in coil scanning in a library area. Patent two (three-dimensional laser SLAM system and control method based on 2D laser radar, CN109358342A) proposes a real-time three-dimensional laser SLAM system and control method based on 2D laser radar, through a 2D laser radar device that rotates at the uniform velocity in succession obtains depth information and rotation angle information simultaneously, carries out the synchronous fusion of the two and generates the three-dimensional point cloud, not only establishes the three-dimensional reconstruction map in real time, and calculates the position and orientation of the sensor through SLAM algorithm, realizes the real-time positioning function, but only is suitable for small scene area, and the ICP algorithm in the used article is sensitive to the initial value.
Disclosure of Invention
The invention provides a warehouse coil position detection system and method based on laser radar, the existing coil detection has the following problems that the scanning precision and the target identification precision are not high, the intelligent transformation of the existing warehouse area is not suitable, the detection is only suitable for a small scene area, the ICP algorithm is sensitive to an initial value, and the like
To solve the above technical problem, an embodiment of the present invention provides the following solutions:
a warehouse coil position detection system based on a laser radar comprises a single-line laser radar, wherein the single-line laser radar is installed on a laser radar adjusting platform, the laser radar adjusting platform is installed under an unmanned overhead traveling crane maintenance platform, the single-line laser radar dynamically scans a warehouse area along with the movement of the unmanned overhead traveling crane maintenance platform, warehouse point cloud information obtained by scanning is transmitted to an unmanned overhead traveling crane industrial personal computer, the unmanned overhead traveling crane industrial personal computer performs data processing on the warehouse point cloud information and then transmits the warehouse point cloud information to a warehouse area management system, and the warehouse area management system is connected with the unmanned overhead traveling crane industrial personal computer, so that three-party communication of the warehouse area management system, the unmanned overhead traveling crane PLC and the single-line laser radar is realized;
a calibration plate is placed in the reservoir area, the single-line laser radar dynamically scans the calibration plate for calibration, external parameters of the single-line laser radar relative to a world coordinate system are obtained, and position and pose transformation is carried out to convert point cloud of the single-line laser radar coordinate system into the world coordinate system; the single-line laser radar dynamically scans the reservoir area, and performs pose transformation by combining the coordinates of the unmanned overhead crane to generate three-dimensional point cloud of the reservoir area; and obtaining the point cloud characteristics of the coil through point cloud processing and characteristic extraction, fitting the target point cloud, calculating the size information of the coil such as the length, the outer diameter and the like, and transmitting the coordinates of the calculated coil under a world coordinate system to a library area management system.
The calibration plate is obliquely placed on the ground, and the normal direction of the plane of the calibration plate is the advancing direction of the unmanned overhead travelling crane.
The laser radar adjusting platform comprises an upper supporting part, a rotating platform is arranged below the upper supporting part, and the rotating platform can rotate around a rotation center.
The system further comprises a flat touch screen, wherein the flat touch screen is connected with the library area management system and used for issuing a single-line laser radar scanning task and confirming a scanning result.
The reservoir area management system is connected with the unmanned crown block manual control machine through the Ethernet.
A warehouse coil position detection method based on laser radar comprises the following steps:
step 1: radar calibration, namely completing the installation of a warehouse coil position detection system based on a laser radar, adjusting a single-line laser radar, obliquely placing a calibration plate in a warehouse coil area, scanning the calibration plate along with the movement of an unmanned overhead traveling crane through the single-line laser radar, generating three-dimensional point cloud by combining the pose of the overhead traveling crane, and performing data processing to obtain an external parameter of a single-line laser radar coordinate system relative to a warehouse area world coordinate system;
step 2: and detecting the position of the coil, namely pressing a scanning start button in a user touch panel by an operator, acquiring a group of point cloud data by the single-line laser radar according to a scanning signal sent by the button in the user touch panel while moving along with the unmanned overhead crane, transmitting the point cloud data information to an information processing server through Ethernet, obtaining the position information of the coil in the reservoir area after point cloud processing and data calculation, and transmitting the position information of the coil in the reservoir area to a reservoir area management system and displaying the position information on the user touch panel.
The radar calibration comprises the following steps:
step 1.1: generating three-dimensional point cloud in the warehouse environment, combining a single-line laser radar coordinate system with the unmanned overhead crane motion pose coordinates output by the unmanned overhead crane PLC, introducing homogeneous coordinates, and performing displacement transformation to form the three-dimensional point cloud in the warehouse environment;
step 1.2: calculating an initially calibrated transformation matrix, screening three-dimensional point clouds in the surrounding environment of the warehouse to obtain ground point clouds and fitting a ground plane, calculating relative variables of a single-line laser radar coordinate system and a warehouse area world coordinate system according to the ground plane, introducing homogeneous coordinates to obtain an initially calibrated transformation matrix, and transforming a plane of the laser radar coordinate system vertical to a Z axis to be coincident with a horizontal plane of the world coordinate system to obtain an initially calibrated coordinate system;
step 1.3: calculating a transformation matrix after secondary calibration, screening the three-dimensional point cloud in the surrounding environment of the warehouse to obtain calibration plate point cloud, performing denoising treatment on the calibration plate point cloud, fitting to obtain a calibration plate plane, and calculating a relative variable of a coordinate system after initial calibration and a library area world coordinate system according to the calibration plate plane to obtain a transformation matrix after secondary calibration;
step 1.4: and calculating a transformation matrix, namely calculating the initially calibrated transformation matrix and the secondarily calibrated transformation matrix to obtain a transformation matrix, storing the transformation matrix, and transforming point cloud data under the single-line laser radar coordinate system to point cloud under a world coordinate system by using the transformation matrix.
Wherein, the coil position detection comprises the following steps:
step 2.1: generating a three-dimensional point cloud of the reservoir area environment, issuing a task by a reservoir area management system, and generating the three-dimensional point cloud of the reservoir area environment by combining the motion pose coordinates of the crown block when the single-line laser radar scans a coil of the reservoir area along with the crown block;
step 2.2: and (3) calculating the position information of the coil, and performing data processing and feature extraction on the three-dimensional point cloud of the coil environment of the coil generated in the step 2.1 to obtain the position information of the coil.
The method for generating the three-dimensional point cloud of the library area environment comprises the following steps:
step 2.1.1: calculating the displacement of the scanning point, namely eliminating the motion distortion of the single-line laser radar in the scanning process along with the overhead traveling crane by combining the pose of the unmanned overhead traveling crane and the scanning period of the single-line laser radar, and calculating the displacement of the scanning point in each scanning period of the single-line laser radar;
step 2.1.2: and (3) coordinate system conversion, namely calculating a scanning point transformation matrix by combining the displacement of the scanning point calculated in the step 2.1.1 and the transformation matrix obtained by calibration, and converting the single-line laser radar coordinate system to a world coordinate system.
The calculation of the position information of the coil in the storage area comprises the following steps:
step 2.2.1: extracting features and denoising, namely extracting an interested point cloud in the point cloud, and denoising the interested point cloud;
step 2.2.2: ground filtering, namely performing ground point cloud filtering processing on the point cloud subjected to noise reduction processing by utilizing the fitted ground plane;
step 2.2.3: segmentation and clustering, namely performing segmentation and clustering on the point cloud processed in the step 2.2.2 to obtain a point cloud cluster;
step 2.2.4: and identifying the coil, namely respectively fitting each point cloud cluster to form a cylinder, calculating the outer diameter and the length of the cylinder, comparing the outer diameter and the length with coil model information sent by a library area management system, taking the minimum error as a coil identification result, sending the coil identification result to the library area management system, and updating the position coordinates of the coil.
The scheme of the invention at least comprises the following beneficial effects:
experiments prove that the warehouse coil position detection method based on the laser radar can accurately generate coil point clouds and accurately detect the shape and the position of a coil, and errors are small. Compared with the scheme of acquiring the position information of the coil by using machine vision, the detection method disclosed by the invention is less influenced by factors such as ambient light and the like, can directly acquire depth information, has higher accuracy and is suitable for indoor large-scene mapping; compared with the scheme of acquiring the position information of the coil by using the multi-line laser radar, the detection method has the advantages of lower cost, more convenient data reading and higher accuracy, and is more suitable for the actual production of enterprises; compared with the mode of performing external reference calibration by adopting the customized calibration block, the detection method provided by the invention performs calibration by using the calibration plate, so that the operation process is simpler, the calibration result can be stored, and the installation error is corrected; the detection system disclosed by the invention has the advantages of simple and clear overall structure, easiness in installation, maintenance and repair, strong algorithm robustness, high calculation speed and high precision, and meets the positioning requirements of most warehouses on the coil.
Drawings
FIG. 1 is a schematic diagram of a lidar-based warehouse coil position detection system in accordance with the present invention;
FIG. 2 is a schematic structural diagram of a lidar adjustment platform of a lidar-based warehouse coil position detection system of the present invention;
FIG. 3 is a three-dimensional point cloud stitching effect diagram of a laser radar-based warehouse coil position detection method of the present invention;
FIG. 4 is a diagram of the calibration results of the lidar-based warehouse coil position detection method of the present invention;
FIG. 5 is a graph of a statistical filtering process result of a lidar-based warehouse coil position detection method of the present invention;
fig. 6 is a ground filtering result diagram of the lidar-based warehouse coil position detection method of the present invention.
Fig. 7 is a point cloud segmentation result diagram of the warehouse coil position detection method based on the laser radar of the present invention.
Reference numerals:
1. a single line laser radar; 2. a laser radar adjusting platform; 21. an upper support portion; 22. rotating the platform; 23. a center of gyration; 3. an unmanned overhead traveling crane overhaul platform; 4. an unmanned overhead traveling crane PLC; 5. an unmanned overhead travelling crane industrial personal computer; 6. a reservoir management system; 7. a flat touch screen; 8. calibrating the plate;
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
In the intelligent warehouse material loading and unloading process, accurate acquisition of the position information of the coil is one of important prerequisites for realizing automatic loading and unloading. Because machine vision receives factors such as light in the environment to influence great, be difficult to adapt to adverse circumstances, the wide application of machine vision technique in the mill has been restricted, and laser radar receives the environmental impact less, has higher precision, can directly acquire depth information, and single line laser radar 1 is lower than multi-thread laser radar cost, this embodiment provides a warehouse line book position detecting system based on laser radar, single line laser radar 1 is along with the mode that overhead traveling crane motion scanning storehouse district line book, accurately acquire the position information of line book. The single-line laser radar 1 moves along with the overhead traveling crane, dynamically scans the environment of the reservoir area, realizes three-dimensional reconstruction of the scene of the reservoir area, accurately identifies the coil information, provides a basis for control decision of lifting and falling of the unmanned overhead traveling crane, and greatly increases the logistics efficiency.
As shown in fig. 1 to 5, the present embodiment provides a system for detecting a position of a warehouse coil based on a laser radar, which includes a single line laser radar 1, a laser radar adjustment platform 2, an unmanned overhead traveling crane overhaul platform 3, an unmanned overhead traveling crane PLC4, an unmanned overhead traveling crane industrial personal computer 5, a warehouse area management system 6, a flat touch screen 7, and a calibration board 8; the single-line laser radar 1 is installed on a laser radar adjusting platform 2, the single-line laser radar 1 dynamically scans a warehouse area along with the movement of an unmanned overhead crane overhauling platform 3, the warehouse area is vertically scanned downwards, a calibration plate 8 is placed in the warehouse area, the calibration plate 8 is obliquely placed on the ground, the normal direction of the plane of the calibration plate is the advancing direction of the unmanned overhead crane, warehouse point cloud information obtained by scanning is transmitted to an unmanned overhead crane industrial personal computer 5, and the unmanned overhead crane industrial personal computer 5 transmits the warehouse point cloud information to a warehouse area management system 6 after data processing is carried out on the warehouse point cloud information; the laser radar adjusting platform 2 is arranged right below the unmanned crown block overhauling platform 3 and moves along with the unmanned crown block overhauling platform 3; the storehouse area management system 6 is connected with the unmanned overhead traveling crane industrial personal computer 5, and the storehouse area management system 6 is connected with the unmanned overhead traveling crane industrial personal computer 5 through the Ethernet, so that three-party communication of the storehouse area management system 6, the unmanned overhead traveling crane PLC4 and the single-line laser radar 1 is realized. The flat touch screen 7 is connected with the reservoir area management system 6, and the flat touch screen 7 is connected with the reservoir area management system 6 through the Ethernet and used for issuing scanning tasks of the single-line laser radar 1 and confirming scanning results.
A calibration plate 8 is placed in the reservoir area, the single-line laser radar 1 dynamically scans the calibration plate 8 for calibration, external reference of the single-line laser radar 1 relative to a world coordinate system is obtained, and position and pose transformation is carried out to convert point cloud of the single-line laser radar 1 coordinate system into the world coordinate system; the single-line laser radar 1 dynamically scans a library area, and performs pose transformation by combining with the coordinates of an unmanned overhead crane to generate a three-dimensional point cloud of the library area; and point cloud characteristics of the coil are obtained through point cloud processing and characteristic extraction, the target point cloud is fitted, size information such as the length and the outer diameter of the coil is calculated, and the coordinate of the calculated coil in a world coordinate system is transmitted to the library area management system 6.
As shown in fig. 2, the laser radar adjustment platform 2 is of an aluminum alloy structure and is installed on the unmanned overhead traveling crane maintenance platform 3 through an angle steel support frame. The laser radar adjustment platform 2 of this embodiment includes support section 21, and support section 21 is accomplished by the aluminum alloy material preparation on, is provided with rotary platform 22 in the below of last support section, and rotary platform 22 can be rotatory round centre of gyration 23, locks behind the adjustment laser radar scanning angle. The single line laser radar 1 is bolted to the rotating platform 22.
The coil position detection system of the embodiment utilizes the single-line laser radar 1 to dynamically scan the reservoir area environment along with the movement of the overhead traveling crane, then carries out filtering preprocessing, cluster analysis and feature extraction on three-dimensional point cloud data, identifies the position information of a target coil, and provides a basis for the movement decision of the lifting and falling of the unmanned overhead traveling crane. After the operator and the stock area management system 6 confirm the scanning task, the invention automatically carries out a series of processes, and finally sends the result to the stock area management system 6 to update the external diameter, the length and the central axis position coordinate of the coil.
The embodiment provides a warehouse coil position detection method based on a laser radar, which comprises the following steps:
step 1: radar calibration, namely completing the installation of a warehouse coil position detection system based on a laser radar, adjusting a single-line laser radar 1, obliquely placing a calibration plate 8 in a warehouse coil area, scanning the calibration plate 8 along with the movement of an unmanned overhead crane through the single-line laser radar 1, generating three-dimensional point cloud by combining the pose of the overhead crane, and performing data processing to obtain an external parameter of a coordinate system of the single-line laser radar 1 relative to a warehouse area world coordinate system;
step 2: and detecting the position of the coil, namely pressing a scanning start button in a user touch panel by an operator, acquiring a group of point cloud data by the single-line laser radar 1 according to a scanning signal sent by the button in the user touch panel while moving along with the unmanned overhead crane, transmitting the point cloud data information to an information processing server through Ethernet, and after point cloud processing and data calculation, sending the coil position detection result to a library area management system 6 and displaying the coil position detection result on the user touch panel.
After the step 1 is finished, when the position of the coil needs to be measured, only the step 2 needs to be executed; and if the installation position, the attitude and the like of the radar are changed, the step 1 is required to be executed again for radar calibration, and the step 2 is executed again for measuring the position of the coil.
In the radar standard-reaching centering in the step 1 of the embodiment, a calibration plate 8 is obliquely placed in a warehouse coil area, the calibration plate 8 is scanned through a single-line laser radar 1 along with the movement of an unmanned overhead crane, three-dimensional point cloud is generated by combining the pose of the overhead crane, then, the data processing is carried out to obtain the external parameters of the single-line laser radar 1 relative to a warehouse area world coordinate system and the external parameters are stored locally, and the point cloud processing and the data calculation are to splice original point cloud data into the three-dimensional point cloud, fit a plane and calculate the calibration parameters. The method comprises the steps of 1.1, generating three-dimensional point cloud in the surrounding environment of a warehouse, 1.2, calculating a transformation matrix of initial calibration, 1.3, calculating the transformation matrix after secondary calibration and 1.4.
Step 1.1: generating three-dimensional point cloud in the surrounding environment of the warehouse, combining a single-line laser radar 1 coordinate system with the unmanned overhead crane motion pose coordinates output by the unmanned overhead crane PLC4, introducing homogeneous coordinates, and performing displacement transformation to form the three-dimensional point cloud in the surrounding environment of the warehouse;
in particular, the scanning plane of the single-line lidar 1 is regarded as the radar coordinate system olxlylzlIn by xlAxis and ylThe plane formed by the axes, i.e. vertically downwards, being the y of the radar coordinate systemlAxis set to z of radar coordinate system along direction of motion of unmanned overhead travelling cranelAxis perpendicular to z in the radar coordinate systemlAxis and ylAxis x of radar coordinate systemlThe axis is the unmanned overhead crane motion pose coordinate x output by the unmanned overhead crane PLC4 according to the coordinate systemc、yc、zcAnd (4) combining, introducing homogeneous coordinates, and performing displacement transformation, as shown in formula-1. A three-dimensional point cloud in the surrounding environment is composed, as shown in fig. 3.
Step 1.2: calculating an initially calibrated transformation matrix, screening three-dimensional point clouds in the surrounding environment of the warehouse to obtain ground point clouds and fitting a ground plane, calculating relative variables of a single-line laser radar 1 coordinate system and a warehouse area world coordinate system according to the ground plane, introducing a homogeneous coordinate to obtain the initially calibrated transformation matrix, and transforming a plane of the laser radar coordinate system vertical to a Z axis to be coincident with a horizontal plane of the world coordinate system to obtain the initially calibrated coordinate system;
specifically, ground point clouds are screened out by using straight-through filtering, a ground plane is fitted by using a RANSAC method to obtain a ground plane fitting equation shown in a formula-2, and a parameter A is obtained according to a ground fitting resultg、Bg、Cg、DgCalculating a single line laser radar 1 coordinate system xlylzlAround the world coordinate system xwywzwIn xwAngle of rotation theta of shaftxAnd ywAngle of rotation theta of shaftyAnd the lidar coordinate system is along the world coordinate system zwTranslation distance t of the shaftzIntroducing homogeneous coordinates to obtain initially calibrated transformation matrix T1X of the lidar coordinate system as shown in equation-3lolylPlane transformation to x of world coordinate systemwowywPlane coincidence is carried out to obtain a coordinate system x after initial calibration1y1z1Wherein x iswDirection to the left, ywThe direction is the same as the projection direction of the normal vector of the fitting plane of the calibration plate 8 on the horizontal plane (namely the advancing direction of the unmanned overhead travelling crane), zwIn a direction vertically upwards owIs a library area coordinate origin defined in the library area management system 6;
Agx+Bgy+Cgz+Dg0 formula-2
Step 1.3: calculating a transformation matrix after secondary calibration, screening the three-dimensional point cloud in the surrounding environment of the warehouse to obtain 8 point cloud of a calibration plate, denoising the 8 point cloud of the calibration plate, fitting to obtain 8 planes of the calibration plate, and calculating relative variables of the initially calibrated coordinate system and a warehouse area world coordinate system according to the 8 planes of the calibration plate to obtain the transformation matrix after secondary calibration;
specifically, straight-through filtering is used for screening out point clouds of a calibration plate 8 which is placed obliquely, noise points are removed through statistical filtering, and then the plane of the calibration plate 8 is fitted through an RANSAC method to obtain a current coordinate system x1y1z1The equation of the lower calibration plate 8 plane is shown in formula-4, and the coordinate system x after initial calibration is calculated according to the parameters of the plane fitting result of the calibration plate 81y1z1Around the world coordinate system zwywzwMiddle zwAngle of rotation thetazAlong xwTranslation t of the shaftxAnd along zwTranslation t of the shaftzObtaining the transformation matrix after the secondary calibrationT2As shown in equation-5, x is added1y1z1Transformation of coordinate system to world coordinate system xwywzw；
Abx+Bby+Cbz+Db0 formula-4
Step 1.4: and (3) calculating a transformation matrix, namely calculating the initially calibrated transformation matrix and the secondarily calibrated transformation matrix to obtain the transformation matrix, storing the transformation matrix, and transforming the point cloud data under the single-line laser radar 1 coordinate system to the point cloud under the world coordinate system by using the transformation matrix.
Specifically, after calibration is completed, the matrix T is transformed1And T2Calculating and storing a transformation matrix T, transforming point cloud data under the coordinate system of the single-line laser radar 1 into a world coordinate system through a formula-6, temporarily setting the origin of the world coordinate system as a projection point A of the angular point of the calibration plate 8 on the ground as shown in FIG. 4 according to a calibration result, and setting a ground plane equation fitting result as follows: -0.083232x-0.996350y +0.018940z +1.348637 is 0, the fit in the plane of the calibration plate 8 is: 0.044279x-0.832118y +0.552828z-0.373667 ═ 0; .
In the process of detecting the position of the coil in the step 2, the single-line laser radar 1 scans the library area, an operator presses a scanning button which is started in a user touch panel, the single-line laser radar 1 collects a group of point cloud data along with the movement of an unmanned overhead crane according to a scanning signal sent by the user touch panel, the point cloud data information is transmitted to an information processing server through an Ethernet, after the point cloud processing and the data calculation, the result is transmitted to a library area management system 6 and displayed on the user touch panel, the point cloud processing and the data calculation comprise the step 2.1 of generating the three-dimensional point cloud of the library area environment and the step 2.2 of calculating the position information of the coil in the library area, wherein the step 2.1 of generating the three-dimensional point cloud of the library area environment comprises the step 2.1.1 of calculating the displacement of a scanning point and the step 2.1.2 of converting; step 2.2, calculating the position information of the coil in the library area, including step 2.2.1, extracting features, denoising, step 2.2.2: ground filtering, step 2.2.3 segmentation clustering, and step 2.2.4 coil identification.
Step 2.1: generating a three-dimensional point cloud of the reservoir area environment, issuing a task by a reservoir area management system 6, and generating the three-dimensional point cloud of the reservoir area environment by combining with the motion pose coordinates of the overhead travelling crane when the single-line laser radar 1 scans a coil of the reservoir area along with the overhead travelling crane;
specifically, the warehouse area management system 6 issues tasks, and when the single-line laser radar 1 scans the warehouse area coil along with the overhead traveling crane, the coordinates x of the motion pose of the overhead traveling crane are combinedc、yc、zcGenerating a three-dimensional point cloud map of the reservoir area environment;
step 2.1.1: calculating the displacement of the scanning point, namely eliminating the motion distortion of the single-line laser radar 1 along with the scanning process of the overhead traveling crane by combining the pose of the unmanned overhead traveling crane and the scanning period of the single-line laser radar 1, and calculating the displacement of the scanning point in each scanning period of the single-line laser radar 1;
specifically, combine unmanned overhead traveling crane position and posture xc、yc、zcAnd a single line laser radar 1 scanning period TlEliminating the motion distortion of the single-line laser radar 1 in the scanning process along with the overhead traveling crane, wherein the motion direction of the unmanned overhead traveling crane is the y of a world coordinate systemwThe direction is interpolated between the pose transmission frequencies of the unmanned overhead travelling crane according to the position information, and the ith scanning point in the nth scanning period of the single-line laser radar 1 is calculated in ywDisplacement in direction
As shown in equation-7, wherein
And
two adjacent times are respectively transmitted by the unmanned overhead travelling crane PLC4 before and after the nth scanning period of the single line laser radar 1ywCoordinate on axis, N being the number of periods of radar scan in a bin scan task, pnumnThe total number of scanning points in the nth scanning period;
step 2.1.2: and (3) coordinate system conversion, namely calculating a scanning point transformation matrix by combining the displacement of the scanning point calculated in the step 2.1.1 and the transformation matrix obtained by calibration, and converting the coordinate system of the single-line laser radar 1 into a world coordinate system.
In particular, y in combination with a scanning spot of the single line lidar 1wAxial displacement
Calculating the transformation matrix T of the ith scanning point in the nth scanning period of the single-line laser radar 1 by using the transformation matrix T stored after the calibrationi nAnd thereby the single-line lidar 1 coordinate system xlylzlTransformation to world coordinate system xwywzwNext, as shown in equation-8;
step 2.2: and (3) calculating the position information of the coil, and performing data processing and feature extraction on the three-dimensional point cloud of the coil environment of the coil generated in the step 2.1 to obtain the position information of the coil.
Step 2.2.1: extracting features and denoising, namely extracting an interested point cloud in the point cloud, and denoising the interested point cloud;
specifically, the region of interest in the point cloud is screened through the pass-through filtering, only the points in the corresponding direction within the threshold range are retained, and the point cloud of the target scanning region is retained, as shown in formula-9, where x iswmin、xwmax、ywmin、ywmax、zwmin、zwmaxAre respectively xw、yw、zwDirectional straight-through filtering threshold range and removing noise points in the point cloud by statistical filtering, as shown in formula-10, assuming that the three-dimensional point cloud follows Gaussian distribution and its shape is determined by the average distance mu and standard deviation sigma between the point and the target point, if the target point and the average distance d of k adjacent pointswkOutside the standard range, the standard range is regarded as outlier removal, and in the invention, the standard range is taken as [ mu-z sigma, mu + z sigma]In this embodiment, z is 1, k is 5, the point clouds before and after filtering are as shown in fig. 5, the left side is the point cloud before statistical filtering, and the right side is the point cloud after statistical filtering;
step 2.2.2: ground filtering, namely performing ground point cloud filtering processing on the point cloud subjected to noise reduction processing by utilizing the fitted ground plane;
specifically, ground filtering is carried out, and after a ground plane is fitted through a RANSAC method, a ground plane equation A is obtainedgx+Bgy+Cgz+DgWhen the point cloud is 0, filtering the ground point cloud, and obtaining the point meeting the condition as shown in formula-11
I.e. the point cloud to be deleted, wherein
The distance from this point to the ground plane, e in this embodimentgThe ground filtering result is shown in fig. 6, the left image is the point cloud before ground filtering, and the right image is the ground point cloud to be filtered;
step 2.2.3: segmentation and clustering, namely performing segmentation and clustering on the point cloud processed in the step 2.2.2 to obtain a point cloud cluster;
specifically, the residual point cloud without ground points is segmented and clustered by the DBSCAN clustering method, and the point cloud is divided into the maximum set of points with connected density, as shown in formula-12, if the target point (x)w，yw，zw) Given radius repsNumber of inner points f (x)w，yw，zw，reps) Greater than a minimum number of points PtsminThen, the clusters are regarded as the same class, the operations are repeated at the points in the radius range, a series of cluster analysis is carried out on the different classes of clusters, firstly, the points with the number less than k are removednumCluster class and coordinate range distribution of (2) and coil size difference dcoorOversized class cluster, and finally outputting a series of class clusters (c)1，c2Λcn) In the present embodiment, PtsminHas a value of 5, knumValue 300, dcoorThe value is 0.5 m;
f(xw，yw，zw，reps)＞Ptsminequation-12
Step 2.2.4: and (4) coil identification, namely respectively fitting each point cloud cluster to form a cylinder, calculating the outer diameter and the length of the cylinder, comparing the outer diameter and the length with coil model information sent by the reservoir area management system 6, taking the minimum error as a coil identification result, sending the coil identification result to the reservoir area management system 6, and updating the position coordinates of the coil.
In particular, point cloud like clusters of pairs (c)1，c2Λcn) Performing cylinder fitting of the RANSAC method, calculating the outer diameter and the length of a cylinder fitting result, comparing the outer diameter and the length with the coil model information sent by the reservoir management system 6, taking the minimum error as a coil identification result, sending the identification result to the reservoir management system 6, and updating the position coordinates of the coil;
the precision of the detection direction of the embodiment is verified, three wire coils with the length of 200mm and the diameter of 50mm are placed on the ground side by side, the single-wire laser radar 1 is made to move along with a guide rail on an experimental platform which is built by itself, a scene below the point cloud is dynamically scanned, a three-dimensional point cloud is generated, the point cloud segmentation result is shown in fig. 7, the point clouds with different gray levels correspond to different wire coil type clusters, and as can be seen from fig. 7, the detection method of the embodiment can accurately generate the wire coil point cloud. The coil model fitting results are shown in table 1; as can be seen from table 1, the detection method of the present embodiment detects the shape and position of the coil more accurately, and has a smaller error.
TABLE 1 precision verification
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. A warehouse coil position detection system based on a laser radar is characterized by comprising a single-line laser radar, wherein the single-line laser radar is installed on a laser radar adjusting platform, the laser radar adjusting platform is installed under an unmanned overhead traveling crane maintenance platform, the single-line laser radar dynamically scans a warehouse area along with the movement of the unmanned overhead traveling crane maintenance platform, warehouse point cloud information obtained by scanning is transmitted to an unmanned overhead traveling crane industrial personal computer, the unmanned overhead traveling crane industrial personal computer performs data processing on the warehouse point cloud information and then transmits the warehouse point cloud information to a warehouse area management system, and the warehouse area management system is connected with the unmanned overhead traveling crane industrial computer, so that three-party communication of the warehouse area management system, the unmanned overhead traveling crane PLC and the single-line laser radar is realized;
a calibration plate is placed in the reservoir area, the single-line laser radar dynamically scans the calibration plate for calibration, external parameters of the single-line laser radar relative to a world coordinate system are obtained, and position and pose transformation is carried out to convert point cloud of the single-line laser radar coordinate system into the world coordinate system; the single-line laser radar dynamically scans the reservoir area, and performs pose transformation by combining the coordinates of the unmanned overhead crane to generate three-dimensional point cloud of the reservoir area; and obtaining the point cloud characteristics of the coil through point cloud processing and characteristic extraction, fitting the target point cloud, calculating the size information of the coil such as the length, the outer diameter and the like, and transmitting the coordinates of the calculated coil under a world coordinate system to a library area management system.
2. The lidar based warehouse coil position sensing system of claim 1, wherein the calibration plate is placed diagonally on the ground with a plane normal direction of the unmanned overhead traveling vehicle.
3. The lidar-based warehouse coil position detection system of claim 1, wherein the lidar adjustment platform comprises an upper support portion below which is disposed a rotating platform that is rotatable about a center of gyration.
4. The lidar-based warehouse coil position detection system of claim 1, further comprising a flat touch screen coupled to the warehouse management system for single line lidar scanning task issuance and scanning result validation.
5. The lidar-based warehouse coil position detection system of claim 1, wherein the warehouse area management system is connected to the unmanned overhead traveling crane operator via an ethernet network.
6. A warehouse coil position detection method based on laser radar is characterized by comprising the following steps:
step 1: radar calibration, namely completing the installation of the warehouse coil position detection system based on the laser radar according to any one of claims 1 to 4, adjusting a single line laser radar, obliquely placing a calibration plate in a warehouse coil area, scanning the calibration plate along with the movement of an unmanned overhead crane through the single line laser radar, generating a three-dimensional point cloud by combining the pose of the overhead crane, and performing data processing to obtain an external parameter of a single line laser radar coordinate system relative to a warehouse area world coordinate system;
step 2: and detecting the position of the coil, namely pressing a scanning start button in a user touch panel by an operator, acquiring a group of point cloud data by the single-line laser radar according to a scanning signal sent by the button in the user touch panel while moving along with the unmanned overhead crane, transmitting the point cloud data information to an information processing server through Ethernet, obtaining the position information of the coil in the reservoir area after point cloud processing and data calculation, and transmitting the position information of the coil in the reservoir area to a reservoir area management system and displaying the position information on the user touch panel.
7. The lidar-based warehouse coil position detection method of claim 6, wherein radar calibration comprises the steps of:
step 1.1: generating three-dimensional point cloud in the warehouse environment, combining a single-line laser radar coordinate system with the unmanned overhead crane motion pose coordinates output by the unmanned overhead crane PLC, introducing homogeneous coordinates, and performing displacement transformation to form the three-dimensional point cloud in the warehouse environment;
step 1.2: calculating an initially calibrated transformation matrix, screening three-dimensional point clouds in the surrounding environment of the warehouse to obtain ground point clouds and fitting a ground plane, calculating relative variables of a single-line laser radar coordinate system and a warehouse area world coordinate system according to the ground plane, introducing homogeneous coordinates to obtain an initially calibrated transformation matrix, and transforming a plane of the laser radar coordinate system vertical to a Z axis to be coincident with a horizontal plane of the world coordinate system to obtain an initially calibrated coordinate system;
step 1.3: calculating a transformation matrix after secondary calibration, screening the three-dimensional point cloud in the surrounding environment of the warehouse to obtain calibration plate point cloud, performing denoising treatment on the calibration plate point cloud, fitting to obtain a calibration plate plane, and calculating a relative variable of a coordinate system after initial calibration and a library area world coordinate system according to the calibration plate plane to obtain a transformation matrix after secondary calibration;
step 1.4: and calculating a transformation matrix, namely calculating the initially calibrated transformation matrix and the secondarily calibrated transformation matrix to obtain a transformation matrix, storing the transformation matrix, and transforming point cloud data under the single-line laser radar coordinate system to point cloud under a world coordinate system by using the transformation matrix.
8. The lidar-based warehouse coil position detection method of claim 6, wherein coil position detection comprises the steps of:
step 2.1: generating a three-dimensional point cloud of the reservoir area environment, issuing a task by a reservoir area management system, and generating the three-dimensional point cloud of the reservoir area environment by combining the motion pose coordinates of the crown block when the single-line laser radar scans a coil of the reservoir area along with the crown block;
step 2.2: and (3) calculating the position information of the coil, and performing data processing and feature extraction on the three-dimensional point cloud of the coil environment of the coil generated in the step 2.1 to obtain the position information of the coil.
9. The lidar-based warehouse coil position detection method of claim 8, wherein the warehouse area environment three-dimensional point cloud generation comprises the steps of:
step 2.1.1: calculating the displacement of the scanning point, namely eliminating the motion distortion of the single-line laser radar in the scanning process along with the overhead traveling crane by combining the pose of the unmanned overhead traveling crane and the scanning period of the single-line laser radar, and calculating the displacement of the scanning point in each scanning period of the single-line laser radar;
step 2.1.2: and (3) coordinate system conversion, namely calculating a scanning point transformation matrix by combining the displacement of the scanning point calculated in the step 2.1.1 and the transformation matrix obtained by calibration, and converting the single-line laser radar coordinate system to a world coordinate system.
10. The lidar-based warehouse coil position detection method of claim 8, wherein the warehouse coil position information calculation comprises the steps of:
step 2.2.1: extracting features and denoising, namely extracting an interested point cloud in the point cloud, and denoising the interested point cloud;
step 2.2.2: ground filtering, namely performing ground point cloud filtering processing on the point cloud subjected to noise reduction processing by utilizing the fitted ground plane;
step 2.2.3: segmentation and clustering, namely performing segmentation and clustering on the point cloud processed in the step 2.2.2 to obtain a point cloud cluster;
step 2.2.4: and identifying the coil, namely respectively fitting each point cloud cluster to form a cylinder, calculating the outer diameter and the length of the cylinder, comparing the outer diameter and the length with coil model information sent by a library area management system, taking the minimum error as a coil identification result, sending the coil identification result to the library area management system, and updating the position coordinates of the coil.
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