WO2021196938A1 - 一种自动化集装箱装卸装置及方法 - Google Patents

一种自动化集装箱装卸装置及方法 Download PDF

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Publication number
WO2021196938A1
WO2021196938A1 PCT/CN2021/078140 CN2021078140W WO2021196938A1 WO 2021196938 A1 WO2021196938 A1 WO 2021196938A1 CN 2021078140 W CN2021078140 W CN 2021078140W WO 2021196938 A1 WO2021196938 A1 WO 2021196938A1
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Prior art keywords
truck
edge
keel
straight line
point cloud
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PCT/CN2021/078140
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English (en)
French (fr)
Inventor
洪俊明
陈环
Original Assignee
上海驭矩信息科技有限公司
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Priority to US17/799,010 priority Critical patent/US11748891B2/en
Publication of WO2021196938A1 publication Critical patent/WO2021196938A1/zh

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C13/00—Other constructional features or details
    • B66C13/18—Control systems or devices
    • B66C13/48—Automatic control of crane drives for producing a single or repeated working cycle; Programme control
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
    • B65G67/00—Loading or unloading vehicles
    • B65G67/02—Loading or unloading land vehicles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
    • B65G69/00—Auxiliary measures taken, or devices used, in connection with loading or unloading
    • B65G69/22—Horizontal loading or unloading platforms
    • B65G69/24—Horizontal loading or unloading platforms having platform level adjusting means
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
    • B65G69/00—Auxiliary measures taken, or devices used, in connection with loading or unloading
    • B65G69/22—Horizontal loading or unloading platforms
    • B65G69/26—Rotatable platforms
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C13/00—Other constructional features or details
    • B66C13/18—Control systems or devices
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
    • B66C13/00—Other constructional features or details
    • B66C13/18—Control systems or devices
    • B66C13/46—Position indicators for suspended loads or for crane elements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/12—Edge-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • G06T7/521—Depth or shape recovery from laser ranging, e.g. using interferometry; from the projection of structured light
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • G06T7/543—Depth or shape recovery from line drawings
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • G06T7/55—Depth or shape recovery from multiple images
    • G06T7/564—Depth or shape recovery from multiple images from contours
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
    • G06V30/10—Character recognition
    • G06V30/19—Recognition using electronic means
    • G06V30/191—Design or setup of recognition systems or techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06V30/19127—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
    • B65G67/00—Loading or unloading vehicles
    • B65G67/02—Loading or unloading land vehicles
    • B65G67/04—Loading land vehicles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10028—Range image; Depth image; 3D point clouds

Definitions

  • the invention relates to the field of crane loading and unloading, in particular to an automated container loading and unloading device and method.
  • the port mostly uses manual operations to load and unload containers on the trucks.
  • the tire crane driver operates the tire crane to perform container loading and unloading operations on the trucks (inner trucks and outer trucks) below them.
  • the shortcomings of the manual operation of the tyre crane driver are the low efficiency of the operation and the unstable operation quality.
  • the container is often smashed into the truck guide plate roughly, which will damage the box and the truck to a certain extent.
  • this approach requires the establishment of a template library for comparison for different types of trucks and different types of car plates, and deviations are prone to occur, resulting in unsuccessful automatic loading and unloading.
  • the technical problem to be solved by the present invention is to provide an automated container loading and unloading device and method.
  • the accuracy of the board is higher, and the amount of calculation is lower.
  • an automated container handling device including:
  • the data acquisition module is used to scan and collect the truck board to obtain laser point cloud data
  • a data preprocessing module configured to segment the acquired laser point cloud data into a laser point cloud on the surface of the collecting truck plate
  • the key point extraction module is used to perform edge extraction on the laser point cloud on the surface of the truck board, so as to obtain discrete points on the edge of the keel of the truck board;
  • the straight line fitting module is used to perform random sampling uniform straight line fitting on the discrete points on the edge of the keel of the truck board, so as to obtain the spatial straight line of the keel of the truck board.
  • the four-dimensional control module is used to linearly control the height of the spreader to be adjusted, the rotation angle of the spreader, the position of the trolley, and the position of the truck to be adjusted according to the space of the edge of the keel of the truck.
  • the data acquisition module is a laser radar
  • the number of the laser radar is at least one
  • the laser radar is installed on the side of the electrical room close to the truck road.
  • the acquiring the spatial straight line of the edge of the truck-collecting plate keel includes acquiring the spatial straight line of one edge of the truck-collecting plate keel.
  • the obtaining the spatial straight line of the edge of the truck-collecting plate keel includes obtaining the spatial straight line of the first edge and the second edge of the truck-collecting plate keel, and judging the space of the first edge Whether the angle between the straight line and the spatial straight line of the second edge is smaller than the preset value, if it is smaller than the preset value, the spatial straight line of the first edge and the spatial straight line of the second edge are merged, otherwise the set is rescanned Truck board to obtain new laser point cloud data.
  • it further includes a space conversion module for horizontally projecting the spatial straight line of the edge of the keel of the truck plate, so as to obtain the height of the spreader, the rotation angle of the spreader, and the position of the trolley. , The position of the collection card that needs to be adjusted.
  • the technical solution adopted by the present invention to solve the above-mentioned technical problems is to provide an automated container loading and unloading method, which includes the following steps:
  • Edge extraction is performed on the laser point cloud on the surface of the truck board, so as to obtain discrete points on the edge of the keel of the truck board;
  • the discrete points on the edge of the truck board keel are randomly sampled and consistent straight line fitting is performed, so as to obtain the spatial straight line of the truck board keel edge.
  • the method further includes the following steps: linearly controlling the height of the spreader to be adjusted, the rotation angle of the spreader, the position of the trolley, and the position of the truck to be adjusted according to the space of the edge of the keel of the truck.
  • the height of the spreader to be adjusted, the rotation angle of the spreader to be adjusted, the position of the trolley to be adjusted, and the position of the truck to be adjusted are linearly controlled according to the space of the edge of the keel of the truck.
  • the scanning collection truck board, the acquisition of laser point cloud data is completed by a data acquisition module, the data acquisition module is a lidar, the number of the lidar is at least one, and the lidar is installed near the electrical room Set the side of the truck road.
  • the acquiring the spatial straight line of the edge of the truck-collecting plate keel includes acquiring the spatial straight line of one edge of the truck-collecting plate keel.
  • the obtaining the spatial straight line of the edge of the truck-collecting plate keel includes obtaining the spatial straight line of the first edge and the second edge of the truck-collecting plate keel, and judging the space of the first edge Whether the angle between the straight line and the spatial straight line of the second edge is smaller than the preset value, if it is smaller than the preset value, the spatial straight line of the first edge and the spatial straight line of the second edge are merged, otherwise the set is rescanned Truck board to obtain new laser point cloud data.
  • the straight line of the space of the edge of the keel of the truck board is horizontally projected, so as to obtain the height of the spreader that needs to be adjusted, the rotation angle of the spreader that needs to be adjusted, the position of the trolley that needs to be adjusted, and the amount of the truck that needs to be adjusted. Location.
  • the present invention has the following beneficial effects: the automated container loading and unloading device and method provided by the present invention, after obtaining laser point cloud data, segment it into the laser point cloud on the surface of the truck plate, and compare the laser point cloud on the surface of the truck plate. Edge extraction of point cloud is used to obtain discrete points on the edge of the truck keel, and random sampling is performed on the discrete points on the edge of the truck keel. It has stronger robustness and higher accuracy. Due to the high performance, the accuracy of loading the container on the truck board is higher and the calculation amount is lower.
  • the spatial straight line of the two edges of the truck plate keel where the spatial straight line of the first edge is used to adjust the height of the spreader, the rotation angle of the spreader, the position of the trolley, and the position of the truck.
  • the edge space line is used to calibrate and merge the space line of the first edge, and determine whether the angle between the space line of the first edge and the space line of the second edge is less than a preset value, if less than With the preset value, the first edge spatial straight line and the second edge spatial straight line are merged, otherwise, the truck board is rescanned to obtain new laser point cloud data, thereby improving the accuracy of automated container loading and unloading.
  • Figure 1 is a schematic structural diagram of an automated container loading and unloading device in an embodiment of the present invention
  • FIG. 2 is a schematic diagram of the structure of the car plate of the automated container loading and unloading device in the embodiment of the present invention
  • Figure 3 is a block diagram of an automated container handling device in an embodiment of the present invention.
  • Figure 4 is a block diagram of an automated container handling device in another embodiment of the present invention.
  • FIG. 5 is a schematic diagram of laser point cloud data acquired by the automated container loading and unloading device in the embodiment of the present invention.
  • FIG. 6 is a schematic diagram of the calculation relationship of the automated container loading and unloading device in the embodiment of the present invention.
  • FIG. 7 is a flowchart of an automated container loading and unloading method in an embodiment of the present invention.
  • Fig. 8 is a flowchart of an automated container loading and unloading method in another embodiment of the present invention.
  • FIG. 1 is a schematic structural diagram of an automated container loading and unloading device in an embodiment of the present invention.
  • the automated container loading and unloading device includes a truck head 1, a truck plate 2, a lidar 5, and a lidar 6
  • the electrical room 7 and the tire crane beam 8 also include laser rays 3 and 4 emitted by lidar 5 and lidar 6.
  • Fig. 2 is a schematic diagram of the structure of the vehicle plate of the automated container loading and unloading device in the embodiment of the present invention.
  • the vehicle plate includes a truck guide plate 9 and a truck plate keel 10. There are two truck plate keels 10 parallel to each other.
  • FIG. 3 is a block diagram of an automated container handling device in an embodiment of the present invention.
  • the automated container loading and unloading device includes: a data collection module 31, used to scan the collection truck board 2 to obtain laser point cloud data; a data preprocessing module 32, used to segment the acquired laser point cloud data into the collection truck board The laser point cloud on the surface; the key point extraction module 33 is used for edge extraction of the laser point cloud on the surface of the truck board, so as to obtain the discrete points on the edge of the keel of the truck board; the straight line fitting module 34, It is used to perform random sampling uniform straight line fitting on the discrete points on the edge of the keel of the truck board, so as to obtain the spatial straight line of the keel of the truck board.
  • the data acquisition module 31 is a laser radar, the number of the laser radar is at least one, and the laser radar is installed on the side of the electrical room close to the truck road.
  • the lidar 5 and the lidar 6 are multi-line lasers, which are distributed at the front and rear ends along the direction of the cart, so that the respective laser rays 3 and 4 of the lidar 5 and the lidar 6 can respectively cover To set part of the truck board 2.
  • FIG. 4 is a block diagram of an automated container handling device in an embodiment of the present invention.
  • it also includes a four-dimensional control module 35 for linearly controlling the height of the spreader to be adjusted, the rotation angle of the spreader to be adjusted, and the position of the trolley that needs to be adjusted according to the space on the edge of the keel of the truck. Adjusted position.
  • Fig. 5 is a schematic diagram of laser point cloud data obtained by the automated container loading and unloading device in an embodiment of the present invention.
  • the lidar 5 and the lidar 6 scan the collecting truck plate 2 to obtain the data falling on the collecting truck plate 2.
  • Two clusters of sparse laser point clouds, each segment of the laser point cloud represents the local features of the truck plate 2.
  • the laser point cloud on the upper surface of the truck plate 2 can be segmented.
  • the laser point cloud on the upper surface of the truck board 2 contains two truck board keels 10 of the truck board 2.
  • edge extraction and straight line fitting are performed on the laser point cloud on the upper surface of the truck board 2 to obtain two straight lines along the outer edges of the two truck board keels 10 of the truck board 2.
  • the acquiring the spatial straight line of the edge of the truck-collecting plate keel includes acquiring the spatial straight line of one edge of the truck-collecting plate keel.
  • the obtaining the spatial straight line of the edge of the truck plate keel includes obtaining the spatial straight line of the first edge and the second edge of the truck plate keel, Determine whether the angle between the spatial straight line of the first edge and the spatial straight line of the second edge is smaller than a preset value, and if it is smaller than the preset value, merge the spatial straight line of the first edge and the second edge
  • the edge of the space is straight, otherwise rescan the collection truck board to obtain new laser point cloud data.
  • the preset value of the included angle between the spatial straight line of the first edge and the spatial straight line of the second edge may be preset, and the preset value may be a value based on experience of a person skilled in the art. Set, if the angle between the space line of the first edge and the space line of the second edge is less than the preset value, the space line of the first edge and the space line of the second edge are merged , Otherwise it means that the error between the obtained first edge and the second edge is large, and the truck board needs to be scanned again to obtain new laser point cloud data.
  • edge extraction is performed on the laser point cloud clusters on the upper surface of the truck board 2.
  • point clouds In this time, by arranging the point clouds in the x, y, and z directions in ascending or descending order, the discrete edges of the truck board keel 10 are obtained.
  • Point. Enter the RANSAC (Random Sample Consensus Random Sample Consensus) straight line fitting to these discrete points, so as to obtain two spatial straight lines along the outer edge of the car keel.
  • RANSAC Random Sample Consensus Random Sample Consensus
  • the space line of the edge of the keel of the truck plate is projected horizontally, so as to obtain the height of the spreader, the rotation angle of the spreader, the position of the trolley, and the truck needs to be adjusted. Adjusted position.
  • the deflection angle of the truck relative to the cart can be obtained.
  • the horizontal displacement relative to the cart can be obtained.
  • the relative displacement of the spreader can be obtained.
  • Vertical displacement, and the position difference along the direction of the cart. In this way, it is converted into the angle at which the spreader needs to rotate, the position where the trolley needs to move, the height at which the spreader needs to drop, and the distance that the truck needs to be guided forward and backward.
  • 501 is a tire crane trolley
  • 502 is a tire crane trolley
  • 503 is a steel wire rope
  • 504 is the distance between the spreader and the truck plate 2 h
  • 505 is the spreader
  • 506 is the linear space translation of the truck plate keel.
  • Auxiliary line 507 is the horizontal projection angle ⁇ between the spreader and the truck plate keel
  • 508 is the edge line of the truck keel
  • 509 is the horizontal projection distance d between the spreader 505 and the truck plate 2 along the direction of the truck 502
  • 510 is the horizontal projection distance x between the spreader 505 and the truck 501 in the direction of the trolley 501
  • 511 is the auxiliary line in the direction of the truck 502
  • 512 is the auxiliary line at the end of the short side of the truck slab 2.
  • IPC Intelligent Personal Computer
  • PLC Programmable Logic Controller
  • the technical solution adopted by the present invention to solve the above-mentioned technical problems is to provide an automated container loading and unloading method, which includes the following steps:
  • Step 601 Scan the collection truck board to obtain laser point cloud data
  • Step 602 Segment the acquired laser point cloud data into the laser point cloud on the surface of the collecting truck board;
  • Step 603 Perform edge extraction on the laser point cloud on the surface of the truck board, so as to obtain discrete points on the edge of the keel of the truck board;
  • Step 604 Perform random sampling uniform straight line fitting on the discrete points on the edge of the keel of the truck board, so as to obtain the spatial straight line of the keel of the truck board.
  • the scanning collection truck board, the acquisition of laser point cloud data is completed by a data acquisition module, the data acquisition module is a lidar, the number of the lidar is at least one, and the lidar is installed near the electrical room Set the side of the truck road.
  • the acquiring the spatial straight line of the edge of the truck-collecting plate keel includes acquiring the spatial straight line of one edge of the truck-collecting plate keel.
  • FIG. 8 is a flowchart of an automated container loading and unloading method in another embodiment of the present invention. It also includes the following steps. Step 605: linearly control the height of the spreader to be adjusted, the rotation angle of the spreader, the position of the trolley, and the position of the truck to be adjusted according to the space of the edge of the keel of the truck.
  • the obtaining the spatial straight line of the edge of the truck-collecting plate keel includes obtaining the spatial straight line of the first edge and the second edge of the truck-collecting plate keel, and judging the space of the first edge Whether the angle between the straight line and the spatial straight line of the second edge is smaller than the preset value, if it is smaller than the preset value, the spatial straight line of the first edge and the spatial straight line of the second edge are merged, otherwise the set is rescanned Truck board to obtain new laser point cloud data.
  • the preset value of the included angle between the spatial straight line of the first edge and the spatial straight line of the second edge may be preset, and the preset value may be a value based on experience of a person skilled in the art. Set, if the angle between the space line of the first edge and the space line of the second edge is less than the preset value, the space line of the first edge and the space line of the second edge are merged , Otherwise it means that the error between the obtained first edge and the second edge is large, and the truck board needs to be scanned again to obtain new laser point cloud data.
  • the straight line of the space of the edge of the keel of the truck board is horizontally projected, so as to obtain the height of the spreader that needs to be adjusted, the rotation angle of the spreader that needs to be adjusted, the position of the trolley that needs to be adjusted, and the amount of the truck that needs to be adjusted. Location.
  • the automated container loading and unloading device and method obtained laser point cloud data, segment it into the laser point cloud on the surface of the collecting truck plate, and perform edge extraction on the laser point cloud on the surface of the collecting truck plate to obtain the laser point cloud data.
  • the discrete points on the edge of the truck plate keel are randomly sampled and consistent linear fitting is performed on the discrete points on the edge of the truck plate keel, so as to obtain the spatial straight line of the truck plate keel edge, and then adjust the height of the spreader,
  • the rotation angle of the spreader, the position of the trolley, and the position of the truck have stronger robustness and higher accuracy, making the loading of the container onto the truck board more accurate and less computationally expensive.
  • the spatial straight line of the two edges of the truck plate keel where the spatial straight line of the first edge is used to adjust the height of the spreader, the rotation angle of the spreader, the position of the trolley, and the position of the truck.
  • the edge space line is used to calibrate and merge the space line of the first edge, and determine whether the angle between the space line of the first edge and the space line of the second edge is less than a preset value, if less than With the preset value, the first edge spatial straight line and the second edge spatial straight line are merged, otherwise, the truck board is rescanned to obtain new laser point cloud data, thereby improving the accuracy of automated container loading and unloading.

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Abstract

一种自动化集装箱装卸装置及装卸方法，该装置包括：数据采集模块（31），用于扫描集卡车板（2），获取激光点云数据；数据预处理模块（32），用于将激光点云数据分割出集卡车板表面的激光点云；关键点提取模块（33），用于对集卡车板表面的激光点云进行边缘提取，获取车板龙骨边缘上的离散的点；直线拟合模块（34），用于对车板龙骨边缘上的离散的点进行随机采样一致性直线拟合，从而获取车板龙骨边缘的空间直线。该集装箱装卸装置及方法，使用集卡车板龙骨边缘的空间直线进行运算处理，具有更强的鲁棒性，更高的准确性，使得集装箱装载到集卡车板的精度更高，计算量更低。

Description

一种自动化集装箱装卸装置及方法 技术领域
本发明涉及起重机装卸领域，尤其涉及一种自动化集装箱装卸装置及方法。
背景技术
目前，港口对集卡进行装卸集装箱多采用人工作业的方式，轮胎吊司机操作轮胎吊对其下方的集卡(内集卡、外集卡)进行集装箱装卸作业。轮胎吊司机进行人工作业的缺点在于作业效率低，且作业质量不稳定，经常出现粗暴地将集装箱砸进集卡导板的情况，对箱子和集卡都有一定的损伤。现有技术中有一些自动化改造方案，例如可以使用激光对集卡轮廓进行扫描，在确定集卡位置后进行集装箱的装卸作业。但是这种做法对于不同型号的集卡及不同型号的车板，需要建立模板库进行比对，并且容易出现偏差，造成自动装卸不成功。
因此有必要提供一种自动化集装箱装卸装置，可以实现对集卡作业的集装箱的自动化装卸。
发明内容
本发明所要解决的技术问题是提供自动化集装箱装卸装置及方法，通过使用集卡车板龙骨边缘的空间直线进行运算处理，具有更强的鲁棒性，更高的准确性，使得集装箱装载到集卡车板的精度更高，计算量更低。
本发明为解决上述技术问题而采用的技术方案是提供一种自动化集装箱装卸装置，包括：
数据采集模块，用于扫描集卡车板，获取激光点云数据；
数据预处理模块，用于将获取的所述激光点云数据分割出所述集卡车板表面的激光点云；
关键点提取模块，用于对所述集卡车板表面的激光点云进行边缘提取，从而获取所述集卡车板龙骨边缘上的离散的点；
直线拟合模块，用于对所述集卡车板龙骨边缘上的离散的点进行随机采样一致性直线拟合，从而获取所述集卡车板龙骨边缘的空间直线。
优选地，四维控制模块，用于根据所述集卡车板龙骨边缘的空间直线控制吊具需要调整的高度、吊具需要调整的旋转角度以及小车需要调整的位置、集卡需要调整的位置。
优选地，所述数据采集模块为激光雷达，所述激光雷达的数量为至少一个，所述激光雷达安装在电气房靠近集卡车道的一侧。
优选地，所述获取所述集卡车板龙骨边缘的空间直线包括获取所述集卡车板龙骨的一条边缘的空间直线。
优选地，所述获取所述集卡车板龙骨边缘的空间直线包括获取所述集卡车板龙骨的第一条边缘的空间直线和第二条边缘的空间直线，判断所述第一条边缘的空间直线和第二条边缘的空间直线之间的夹角是否小于预设值，如果小于预设值，则融合所述第一条边缘的空间直线和第二条边缘的空间直线，否则重新扫描集卡车板，获取新的激光点云数据。
优选地，还包括空间转换模块，用于将所述集卡车板龙骨边缘的空间直线进行水平投影，从而获取吊具需要调整的高度、所述吊具需要调整的旋转角度以及小车需要调整的位置、所述集卡需要调整的位置。
本发明为解决上述技术问题而还采用的技术方案是提供一种自动化集装箱装卸方法，包括以下步骤：
扫描集卡车板，获取激光点云数据；
将获取的所述激光点云数据分割出所述集卡车板表面的激光点云；
对所述集卡车板表面的激光点云进行边缘提取，从而获取所述集卡车板龙骨边缘上的离散的点；
对所述集卡车板龙骨边缘上的离散的点进行随机采样一致性直线拟合，从而获取所述集卡车板龙骨边缘的空间直线。
优选地，还包括以下步骤：根据所述集卡车板龙骨边缘的空间直线控制吊具需要调整的高度、吊具需要调整的旋转角度以及小车需要调整的位置、集卡需要调整的位置。
根据所述集卡车板龙骨边缘的空间直线控制吊具需要调整的高度、吊具需要调整的旋转角度以及小车需要调整的位置、集卡需要调整的位置。
优选地，所述扫描集卡车板，获取激光点云数据通过数据采集模块来完成，所 述数据采集模块为激光雷达，所述激光雷达的数量为至少一个，所述激光雷达安装在电气房靠近集卡车道的一侧。
优选地，所述获取所述集卡车板龙骨边缘的空间直线包括获取所述集卡车板龙骨的一条边缘的空间直线。
优选地，所述获取所述集卡车板龙骨边缘的空间直线包括获取所述集卡车板龙骨的第一条边缘的空间直线和第二条边缘的空间直线，判断所述第一条边缘的空间直线和第二条边缘的空间直线之间的夹角是否小于预设值，如果小于预设值，则融合所述第一条边缘的空间直线和第二条边缘的空间直线，否则重新扫描集卡车板，获取新的激光点云数据。
优选地，将所述集卡车板龙骨边缘的空间直线进行水平投影，从而获取吊具需要调整的高度、所述吊具需要调整的旋转角度以及小车需要调整的位置、所述集卡需要调整的位置。
本发明对比现有技术有如下的有益效果：本发明提供的自动化集装箱装卸装置及方法，获取激光点云数据后，将其分割出集卡车板表面的激光点云，对集卡车板表面的激光点云进行边缘提取，获取集卡车板龙骨边缘上的离散的点，对集卡车板龙骨边缘上的离散的点进行随机采样一致性直线拟合，具有更强的鲁棒性，更高的准确性，使得集装箱装载到集卡车板的精度更高，计算量更低。
进一步地，获取集卡车板龙骨的两条边缘的空间直线，其中第一条边缘的空间直线用于调整吊具的高度、吊具的旋转角度以及小车的位置、集卡的位置，第二条边缘的空间直线用于对第一条边缘的空间直线进行校准与融合，判断所述第一条边缘的空间直线和第二条边缘的空间直线之间的夹角是否小于预设值，如果小于预设值，则融合所述第一条边缘的空间直线和第二条边缘的空间直线，否则重新扫描集卡车板，获取新的激光点云数据，从而提高自动化集装箱装卸的准确性。
附图说明
图1为本发明实施例中自动化集装箱的装卸装置的结构示意图；
图2为本发明实施例中自动化集装箱的装卸装置的车板结构示意图；
图3为本发明实施例中自动化集装箱装卸装置的模块图；
图4为本发明又一实施例中自动化集装箱装卸装置的模块图；
图5为本发明实施例中自动化集装箱的装卸装置获取的激光点云数据的示意图；
图6为本发明实施例中自动化集装箱的装卸装置的计算关系示意图；
图7为本发明实施例中自动化集装箱装卸方法的流程图；
图8为本发明又一实施例中自动化集装箱装卸方法的流程图。
具体实施方式
下面结合附图和实施例对本发明作进一步的描述。
在以下描述中，为了提供本发明的透彻理解，阐述了很多具体的细节。然而，本发明可以在没有这些具体的细节的情况下实践，这对本领域普通该技术人员来说将是显而易见的。因此，具体的细节阐述仅仅是示例性的，具体的细节可以由奔放的精神和范围而变化并且仍被认为是在本发明的精神和范围内。
现在参看图1至图3，图1为本发明实施例中自动化集装箱的装卸装置的结构示意图，所述自动化集装箱的装卸装置包括集卡车头1、集卡车板2、激光雷达5、激光雷达6、电气房7以及轮胎吊大梁8，还包括由激光雷达5和激光雷达6发射的激光射线3和激光射线4。
图2是本发明实施例中自动化集装箱的装卸装置的车板结构示意图，车板包括集卡导板9和集卡车板龙骨10，集卡车板龙骨10有两根且相互平行。
现在参看图3，图3是本发明实施例中自动化集装箱装卸装置的模块图。自动化集装箱装卸装置，包括：数据采集模块31，用于扫描集卡车板2，获取激光点云数据；数据预处理模块32，用于将获取的所述激光点云数据分割出所述集卡车板表面的激光点云；关键点提取模块33，用于对所述集卡车板表面的激光点云进行边缘提取，从而获取所述集卡车板龙骨边缘上的离散的点；直线拟合模块34，用于对所述集卡车板龙骨边缘上的离散的点进行随机采样一致性直线拟合，从而获取所述集卡车板龙骨边缘的空间直线。
所述数据采集模块31为激光雷达，所述激光雷达的数量为至少一个，所述激光雷达安装在电气房靠近集卡车道的一侧。
在具体实施中，激光雷达5和激光雷达6为多线激光，其分布在沿大车方向的前后两端，使得激光雷达5和激光雷达6的各自的激光射线3和激光射线4能分别 覆盖到集卡车板2的一部分。
现在参看图4，图4是本发明实施例中自动化集装箱装卸装置的模块图。在具体实施中，还包括四维控制模块35，用于根据所述集卡车板龙骨边缘的空间直线控制吊具需要调整的高度、吊具需要调整的旋转角度以及小车需要调整的位置、集卡需要调整的位置。
现在参看图5，图5是本发明实施例中自动化集装箱的装卸装置获取的激光点云数据的示意图，激光雷达5和激光雷达6通过扫描集卡车板2，得到落在集卡车板2上的两簇稀疏激光点云，每一段激光点云表示集卡车板2的局部特征。对两端激光点云进行平面拟合，即可分割出集卡车板2上表面的激光点云。集卡车板2上表面的激光点云包含了集卡车板2的两根集卡车板龙骨10。再对集卡车板2上表面的激光点云进行边缘提取及直线拟合，即可得到沿着集卡车板2的两根集卡车板龙骨10外边缘的两条直线。
在具体实施中，所述获取所述集卡车板龙骨边缘的空间直线包括获取所述集卡车板龙骨的一条边缘的空间直线。
然而，为了进一步进行数据核对，提高准确率，所述获取所述集卡车板龙骨边缘的空间直线包括获取所述集卡车板龙骨的第一条边缘的空间直线和第二条边缘的空间直线，判断所述第一条边缘的空间直线和第二条边缘的空间直线之间的夹角是否小于预设值，如果小于预设值，则融合所述第一条边缘的空间直线和第二条边缘的空间直线，否则重新扫描集卡车板，获取新的激光点云数据。
在具体实施中，所述第一条边缘的空间直线和第二条边缘的空间直线之间的夹角的预设值可以是预设的，该预设值可以是本领域技术人员根据经验值设定的，如果第一条边缘的空间直线和第二条边缘的空间直线之间的夹角小于该预设值，则融合所述第一条边缘的空间直线和第二条边缘的空间直线，否则说明获取的第一条边缘的空间直线和第二条边缘的空间直线误差较大，则需要重新扫描集卡车板，获取新的激光点云数据。其中，对两端激光点云的平面拟合，需要先将两簇激光点云校准到同一坐标系下，进行点云的前融合，再通过设置车板点云平面与空间铅锤平面的约束关系，调整拟合点的空间距离阈值，进行平面分割，从而得到车板上表面的激光点云簇。
进一步地，对集卡车板2上表面的激光点云簇进行边缘提取，此时通过对点云 的x，y，z方向的组合升序或降序排列，得到集卡车板龙骨10的边缘上的离散的点。进入对这些离散的点进行RANSAC(Random Sample Consensus随机采样一致性)直线拟合，从而得到沿车板龙骨外边缘的两条空间直线。
在具体实施中，将所述集卡车板龙骨边缘的空间直线进行水平投影，从而获取吊具需要调整的高度、所述吊具需要调整的旋转角度以及小车需要调整的位置、所述集卡需要调整的位置。
由上面得到的两根沿车板龙骨外边缘的直线，结合两个激光雷达的标定校准，即可得到集卡相对于大车的偏转角度，相对于大车的水平位移，相对于吊具的垂直位移，以及沿大车方向的位差。从而换算成吊具需要旋转的角度，小车需要移动的位置，吊具需要下降的高度，以及需要指导集卡前进后退的距离。
具体地，参看图6，501为轮胎吊小车，502为轮胎吊大车，503为钢丝绳，504为吊具到集卡车板2距离h，505为吊具，506为集卡车板龙骨直线空间平移辅助线，507为吊具与集卡车板龙骨直线水平投影夹角θ，508为集卡车板龙骨边缘直线，509为吊具505与集卡车板2之间沿大车502方向的水平投影距离d，510为吊具505到集卡车板2之间沿小车501方向的水平投影距离x，511为大车502方向辅助线，512为集卡车板2短边末端辅助线。
当得到集卡车板龙骨外边缘空间直线时，通过空间变换，即可得到吊具需要旋转的角度θ507，小车需要移动的位置x510，吊具需要下降的高度h504，以及需要指导集卡前进后退的距离d509。
最后通过IPC(Industrial Personal Computer，工控机)输出控制指令给PLC(Programmable Logic Controller，可编程逻辑控制器)，PLC中运行先进控制算法控制吊具旋转，小车移动，吊具下降到指定位置；并且IPC输出指示给指示面板，指示集卡应该向前或向后移动的距离。从而完成对集卡自动装卸作业。
现在参看图7，本发明为解决上述技术问题而还采用的技术方案是提供一种自动化集装箱装卸方法，包括以下步骤：
步骤601：扫描集卡车板，获取激光点云数据；
步骤602：将获取的所述激光点云数据分割出所述集卡车板表面的激光点云；
步骤603：对所述集卡车板表面的激光点云进行边缘提取，从而获取所述集卡车板龙骨边缘上的离散的点；
步骤604：对所述集卡车板龙骨边缘上的离散的点进行随机采样一致性直线拟合，从而获取所述集卡车板龙骨边缘的空间直线。
优选地，所述扫描集卡车板，获取激光点云数据通过数据采集模块来完成，所述数据采集模块为激光雷达，所述激光雷达的数量为至少一个，所述激光雷达安装在电气房靠近集卡车道的一侧。
优选地，所述获取所述集卡车板龙骨边缘的空间直线包括获取所述集卡车板龙骨的一条边缘的空间直线。
现在参看图8，图8为本发明又一实施例中自动化集装箱装卸方法的流程图。还包括以下步骤，步骤605：根据所述集卡车板龙骨边缘的空间直线控制吊具需要调整的高度、吊具需要调整的旋转角度以及小车需要调整的位置、集卡需要调整的位置。
优选地，所述获取所述集卡车板龙骨边缘的空间直线包括获取所述集卡车板龙骨的第一条边缘的空间直线和第二条边缘的空间直线，判断所述第一条边缘的空间直线和第二条边缘的空间直线之间的夹角是否小于预设值，如果小于预设值，则融合所述第一条边缘的空间直线和第二条边缘的空间直线，否则重新扫描集卡车板，获取新的激光点云数据。
在具体实施中，所述第一条边缘的空间直线和第二条边缘的空间直线之间的夹角的预设值可以是预设的，该预设值可以是本领域技术人员根据经验值设定的，如果第一条边缘的空间直线和第二条边缘的空间直线之间的夹角小于该预设值，则融合所述第一条边缘的空间直线和第二条边缘的空间直线，否则说明获取的第一条边缘的空间直线和第二条边缘的空间直线误差较大，则需要重新扫描集卡车板，获取新的激光点云数据。
优选地，将所述集卡车板龙骨边缘的空间直线进行水平投影，从而获取吊具需要调整的高度、所述吊具需要调整的旋转角度以及小车需要调整的位置、所述集卡需要调整的位置。
综上，本实施例提供的自动化集装箱装卸装置及方法，获取激光点云数据后，将其分割出集卡车板表面的激光点云，对集卡车板表面的激光点云进行边缘提取，获取集卡车板龙骨边缘上的离散的点，对集卡车板龙骨边缘上的离散的点进行随机采样一致性直线拟合，从而获取所述集卡车板龙骨边缘的空间直线，进而调整吊具 的高度、吊具的旋转角度以及小车的位置、集卡的位置，具有更强的鲁棒性，更高的准确性，使得集装箱装载到集卡车板的精度更高，计算量更低。
进一步地，获取集卡车板龙骨的两条边缘的空间直线，其中第一条边缘的空间直线用于调整吊具的高度、吊具的旋转角度以及小车的位置、集卡的位置，第二条边缘的空间直线用于对第一条边缘的空间直线进行校准与融合，判断所述第一条边缘的空间直线和第二条边缘的空间直线之间的夹角是否小于预设值，如果小于预设值，则融合所述第一条边缘的空间直线和第二条边缘的空间直线，否则重新扫描集卡车板，获取新的激光点云数据，从而提高自动化集装箱装卸的准确性。
虽然本发明已以较佳实施例揭示如上，然其并非用以限定本发明，任何本领域技术人员，在不脱离本发明的精神和范围内，当可作些许的修改和完善，因此本发明的保护范围当以权利要求书所界定的为准。

Claims (12)

  1. 一种自动化集装箱装卸装置，其特征在于，包括：
    数据采集模块，用于扫描集卡车板，获取激光点云数据；
    数据预处理模块，用于将获取的所述激光点云数据分割出所述集卡车板表面的激光点云；
    关键点提取模块，用于对所述集卡车板表面的激光点云进行边缘提取，从而获取所述集卡车板龙骨边缘上的离散的点；
    直线拟合模块，用于对所述集卡车板龙骨边缘上的离散的点进行随机采样一致性直线拟合，从而获取所述集卡车板龙骨边缘的空间直线。
  2. 根据权利要求1所述的自动化集装箱装卸装置，其特征在于，还包括：
    四维控制模块，用于根据所述集卡车板龙骨边缘的空间直线控制吊具需要调整的高度、吊具需要调整的旋转角度以及小车需要调整的位置、集卡需要调整的位置。
  3. 根据权利要求1所述的自动化集装箱装卸装置，其特征在于，所述数据采集模块为激光雷达，所述激光雷达的数量为至少一个，所述激光雷达安装在电气房靠近集卡车道的一侧。
  4. 根据权利要求1所述的自动化集装箱装卸装置，其特征在于，所述获取所述集卡车板龙骨边缘的空间直线包括获取所述集卡车板龙骨的一条边缘的空间直线。
  5. 根据权利要求1所述的自动化集装箱装卸装置，其特征在于，所述获取所述集卡车板龙骨边缘的空间直线包括获取所述集卡车板龙骨的第一条边缘的空间直线和第二条边缘的空间直线，判断所述第一条边缘的空间直线和第二条边缘的空间直线之间的夹角是否小于预设值，如果小于预设值，则融合所述第一条边缘的空间直线和第二条边缘的空间直线，否则重新扫描集卡车板，获取新的激光点云数据。
  6. 根据权利要求1所述的自动化集装箱装卸装置，其特征在于，还包括空间转换模块，用于将所述集卡车板龙骨边缘的空间直线进行水平投影，从而获取吊具需要调整的高度、所述吊具需要调整的旋转角度以及小车需要调整的位置、所述集卡需要调整的位置。
  7. 一种自动化集装箱装卸方法，其特征在于，包括以下步骤：
    扫描集卡车板，获取激光点云数据；
    将获取的所述激光点云数据分割出所述集卡车板表面的激光点云；
    对所述集卡车板表面的激光点云进行边缘提取，从而获取所述集卡车板龙骨边缘上的离散的点；
    对所述集卡车板龙骨边缘上的离散的点进行随机采样一致性直线拟合，从而获取所述集卡车板龙骨边缘的空间直线。
  8. 根据权利要求7所述的自动化集装箱装卸方法，其特征在于，还包括以下步骤：
    根据所述集卡车板龙骨边缘的空间直线控制吊具需要调整的高度、吊具需要调整的旋转角度以及小车需要调整的位置、集卡需要调整的位置。
  9. 根据权利要求7所述的自动化集装箱装卸方法，其特征在于，所述扫描集卡车板，获取激光点云数据通过数据采集模块来完成，所述数据采集模块为激光雷达，所述激光雷达的数量为至少一个，所述激光雷达安装在电气房靠近集卡车道的一侧。
  10. 根据权利要求7所述的自动化集装箱装卸方法，其特征在于，所述获取所述集卡车板龙骨边缘的空间直线包括获取所述集卡车板龙骨的一条边缘的空间直线。
  11. 根据权利要求7所述的自动化集装箱装卸方法，其特征在于，所述获取所述集卡车板龙骨边缘的空间直线包括获取所述集卡车板龙骨的第一条边缘的空间直线和第二条边缘的空间直线，判断所述第一条边缘的空间直线和第二条边缘的空间直线之间的夹角是否小于预设值，如果小于预设值，则融合所述第一条边缘的空间直线和第二条边缘的空间直线，否则重新扫描集卡车板，获取新的激光点云数据。
  12. 根据权利要求7所述的自动化集装箱装卸方法，其特征在于，将所述集卡车板龙骨边缘的空间直线进行水平投影，从而获取吊具需要调整的高度、所述吊具需要调整的旋转角度以及小车需要调整的位置、所述集卡需要调整的位置。
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Families Citing this family (6)

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Publication number Priority date Publication date Assignee Title
CN111115300B (zh) 2020-03-31 2020-06-30 上海驭矩信息科技有限公司 一种自动化集装箱装卸装置及方法
CN111704035B (zh) * 2020-07-02 2022-06-14 上海驭矩信息科技有限公司 一种基于机器视觉的集装箱装卸集卡自动定位装置及方法
CN111830526B (zh) * 2020-09-17 2020-12-29 上海驭矩信息科技有限公司 一种基于多线激光数据融合的集装箱定位方法及装置
CN112859088B (zh) * 2021-01-04 2022-11-11 北京科技大学 一种基于三维雷达的车辆位置信息获取方法及***
CN115817538B (zh) * 2023-01-09 2023-05-16 杭州飞步科技有限公司 无人集卡的控制方法、装置、设备及介质
CN117011503B (zh) * 2023-08-07 2024-05-28 青岛星美装饰服务有限公司 一种加工数据确定方法、装置、设备和可读存储介质

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20100058282A (ko) * 2008-11-24 2010-06-03 주식회사 지팬스 컨테이너의 3차원 표면 영상획득 시스템
CN104200212A (zh) * 2014-06-25 2014-12-10 西安煤航信息产业有限公司 一种基于机载LiDAR数据的建筑物外边界线提取方法
CN108828518A (zh) * 2018-03-29 2018-11-16 上海大学 一种货车车厢内部堆垛车定位方法
CN108932736A (zh) * 2018-05-30 2018-12-04 南昌大学 二维激光雷达点云数据处理方法以及动态机器人位姿校准方法
CN110142805A (zh) * 2019-05-22 2019-08-20 武汉爱速达机器人科技有限公司 一种基于激光雷达的机器人末端校准方法
EP3613699A1 (en) * 2018-08-24 2020-02-26 LASE Industrielle Lasertechnik GmbH Inspection system for container
CN111115300A (zh) * 2020-03-31 2020-05-08 上海驭矩信息科技有限公司 一种自动化集装箱装卸装置及方法

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6201203B1 (en) * 1999-05-12 2001-03-13 Northrop Grumman Corporation Robotic containerization system
CN111288930A (zh) * 2018-11-20 2020-06-16 北京图森智途科技有限公司 一种挂车夹角的测量方法、装置及车辆
CN109959352A (zh) * 2019-03-01 2019-07-02 武汉光庭科技有限公司 利用激光点云计算卡车车头和挂车之间夹角的方法及***
CN113432553B (zh) * 2020-03-23 2023-06-16 北京图森智途科技有限公司 一种挂车夹角的测量方法、装置及车辆

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20100058282A (ko) * 2008-11-24 2010-06-03 주식회사 지팬스 컨테이너의 3차원 표면 영상획득 시스템
CN104200212A (zh) * 2014-06-25 2014-12-10 西安煤航信息产业有限公司 一种基于机载LiDAR数据的建筑物外边界线提取方法
CN108828518A (zh) * 2018-03-29 2018-11-16 上海大学 一种货车车厢内部堆垛车定位方法
CN108932736A (zh) * 2018-05-30 2018-12-04 南昌大学 二维激光雷达点云数据处理方法以及动态机器人位姿校准方法
EP3613699A1 (en) * 2018-08-24 2020-02-26 LASE Industrielle Lasertechnik GmbH Inspection system for container
CN110142805A (zh) * 2019-05-22 2019-08-20 武汉爱速达机器人科技有限公司 一种基于激光雷达的机器人末端校准方法
CN111115300A (zh) * 2020-03-31 2020-05-08 上海驭矩信息科技有限公司 一种自动化集装箱装卸装置及方法

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