CN112816976A - Container door orientation detection method and system, storage medium and electronic device - Google Patents
Container door orientation detection method and system, storage medium and electronic device Download PDFInfo
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- CN112816976A CN112816976A CN202110130651.2A CN202110130651A CN112816976A CN 112816976 A CN112816976 A CN 112816976A CN 202110130651 A CN202110130651 A CN 202110130651A CN 112816976 A CN112816976 A CN 112816976A
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Abstract
The application provides a container door orientation detection method and system, a storage medium and electronic equipment, and solves the technical problems that in the prior art, when a lifting appliance grabs or releases a container, the side of the container door is manually checked, the labor cost is increased, and the loading and unloading time of the container is prolonged. The application provides a container door orientation detection method, the radar has been adopted to detect the first point cloud data combination second point cloud data set of container both sides, and calculate the dispersion of the point cloud data set of container both sides, through judging the big or small relation between the first point cloud dispersion of first point cloud data set and the second point cloud dispersion of second point cloud data set, the container side that corresponds with the point cloud dispersion height then is container door place side, thereby can snatch the in-process that perhaps releases can automated inspection container door place side to the container at the hoist, artifical cost has been reduced, the handling efficiency of container has been improved.
Description
Technical Field
The application relates to the field of engineering machinery, in particular to a container door orientation detection method and system, a storage medium and electronic equipment.
Background
Along with globalization economic development, container logistics transportation increases fast, adopts container transportation goods to have fast convenient, goods safety, low-loss, transportation standardization, be suitable for advantages such as transportation mode extensively, obtains promoting increasingly popularizing, and the handling operation of container mainly can be divided into two links: 1. the loading and unloading operation of the whole container comprises the operations of lifting, reloading, tamping, stacking and the like of the container; 2. the loading and unloading operation of the goods in the container comprises the landing loading and unloading of common goods, the vertical rotation loading and unloading of dry and scattered goods and the like.
In the prior art, the orientation of the container door is often required to be consistent when the containers in the automatic storage yard are placed, so that the requirement on the orientation detection of the container door is met. When adopting the hoist to load and unload the container, need adopt the hoist to snatch or release the container, and snatch or the in-process of releasing at the hoist to the container, because there is the door handle on chamber door one side, the door handle is probably swept to the radar, can lead to the radar to produce the erroneous judgement. Therefore, the box door has larger interference to the box stacking direction, and the box stacking effect is influenced.
Therefore, in the prior art, the side of the container door is judged manually, the labor cost is increased, and the time for loading and unloading the container is prolonged.
Disclosure of Invention
In view of this, the present application provides a method and a system for detecting a container door orientation, a storage medium, and an electronic device, which solve the technical problems of the prior art that when a spreader grabs or releases a container, the side of the container door is manually checked, which increases the labor cost and prolongs the loading and unloading time of the container.
For the purpose of making the present application more apparent, its objects, technical means and advantages will be further described in detail with reference to the accompanying drawings.
According to one aspect of the present application, there is provided a container door orientation detecting method, including: acquiring a first point cloud data set of the surrounding environment of a first side of a container and a second point cloud data set of the surrounding environment of a second side of the container, wherein a container door is arranged on the first side of the container or the second side of the container; respectively acquiring a first point cloud dispersion of the first point cloud data set and a second point cloud dispersion of the second point cloud data set according to the first point cloud data set and the second point cloud data set; when the first point cloud dispersion is larger than the second point cloud dispersion, generating information that the container door is positioned at the first side of the container; and when the second point cloud dispersion is greater than the first point cloud dispersion, generating information that the container door is positioned at the second side of the container.
In one possible implementation, when the first point cloud dispersion is greater than the second point cloud dispersion, generating information that the container door is located on the first side of the container includes: when the first point cloud dispersion is larger than the second point cloud dispersion and the first point cloud dispersion is larger than a first preset value, generating information that the container door is positioned at the first side of the container; when the second point cloud dispersion is greater than the first point cloud dispersion, generating information that the container door is located at the second side of the container, including: and when the second point cloud dispersion is greater than the first point cloud dispersion and the second point cloud dispersion is greater than the first preset value, generating information that the container door is located on the second side of the container.
In a possible implementation manner, obtaining a first point cloud dispersion of the first point cloud data set and a second point cloud dispersion of the second point cloud data set according to the first point cloud data set and the second point cloud data set respectively includes: filtering and straight line fitting are carried out on the first point cloud data group, and a first fitted straight line is generated; acquiring a vertical distance between each first point cloud data in the first point cloud data group and the first fitting straight line, and acquiring a first point cloud dispersion of the first point cloud data group according to the vertical distance between each first point cloud data and the first fitting straight line; filtering and straight line fitting are carried out on the second point cloud data group, and a second fitted straight line is generated; and acquiring the vertical distance between each second point cloud data in the second point cloud data set and the second fitting straight line, and acquiring the second point cloud dispersion of the second point cloud data set according to the vertical distance between each second point cloud data and the second fitting straight line.
In a possible implementation manner, after obtaining a first point cloud dispersion of the first point cloud data set and a second point cloud dispersion of the second point cloud data set according to the first point cloud data set and the second point cloud data set, respectively, the method for detecting a door orientation of a container further includes: acquiring a first-side box door point cloud data reference line and a second-side non-box door point cloud data reference line when a box door of a standard container is positioned at a first side of the standard container; acquiring a point cloud data reference line of a door of a second side door and a point cloud data reference line of a non-door of a first side when the door of the standard container is positioned at the second side of the standard container; wherein, when the first point cloud dispersion is greater than the second point cloud dispersion, generating information that the container door is located at the first side of the container further comprises: when the first point cloud dispersion is larger than the second point cloud dispersion, and the vertical distance between the first fitting straight line and the first side door point cloud data reference line is smaller than the vertical distance between the first fitting straight line and the first side non-door point cloud data reference line, generating information that the container door is positioned at the first side of the container; when the second point cloud dispersion is greater than the first point cloud dispersion, generating information that the container door is located at the second side of the container, including: and when the second point cloud dispersion is greater than the first point cloud dispersion and the vertical distance between the second fitting straight line and the second side door point cloud data reference line is smaller than the vertical distance between the second fitting straight line and the second side non-door point cloud data reference line, generating information that the container door is positioned at the second side of the container.
In one possible implementation, the method for obtaining a first side door point cloud data reference line and a second side non-door point cloud data reference line when a standard container door is located on a first side of a standard container includes: when a door of a standard container is positioned at a first side of the standard container, acquiring a first reference point cloud data set of the surrounding environment of the first side of the standard container and a second reference point cloud data set of the surrounding environment of a second side of the standard container; filtering and straight line fitting are respectively carried out on the first reference point cloud data set and the second reference point cloud data set, and a first side box door point cloud data reference line and a second side non-box door point cloud data reference line are generated; acquiring a first side non-container door point cloud data reference line and a second side container door point cloud data reference line when a standard container door is positioned on a second side of the standard container, wherein the acquiring comprises the following steps: when a door of a standard container is positioned at a second side of the standard container, a third reference point cloud data set of the surrounding environment of the second side of the standard container and a fourth reference point cloud data set of the surrounding environment of the first side of the standard container are obtained; and filtering and straight line fitting are respectively carried out on the third reference point cloud data group and the fourth reference point cloud data group, and a second side box door point cloud data reference line and a first side non-box door point cloud data reference line are generated.
In one possible implementation manner, obtaining the first point cloud dispersion of the first point cloud data group according to the vertical distance between each first point cloud data and the first fitted straight line includes: according to the vertical distance between each first point cloud data and the first fitting straight line, obtaining a first average value of the vertical distance between each first point cloud data and the first fitting straight line; wherein the first point cloud dispersion comprises the first average; acquiring second point cloud dispersion of the second point cloud data set according to the vertical distance between each second point cloud data and the second fitting straight line, wherein the second point cloud dispersion comprises: acquiring a second average value of the vertical distance between each second point cloud data and the second fitting straight line according to the vertical distance between each second point cloud data and the second fitting straight line; wherein the second point cloud dispersion comprises the second average.
In one possible implementation, after acquiring a first point cloud data set of an ambient environment of a first side of a container and a second point cloud data set of an ambient environment of a second side of the container, and before acquiring a first point cloud dispersion of the first point cloud data set and a second point cloud dispersion of the second point cloud data set according to the first point cloud data set and the second point cloud data set, respectively, the method for detecting the orientation of the container door further includes: extracting a point cloud data set in a first preset region of interest from the first point cloud data set to generate a first effective point cloud data set; extracting a point cloud data set in a second preset interest area from the second point cloud data set to generate a second effective point cloud data set; wherein obtaining a first point cloud dispersion of the first point cloud data set according to the first point cloud data set comprises: acquiring a first point cloud dispersion of the first effective point cloud data set according to the first effective point cloud data set; obtaining a second point cloud dispersion of the second point cloud data set according to the second point cloud data set comprises: and acquiring second point cloud dispersion of the second effective point cloud data set according to the second effective point cloud data set.
As a second aspect of the present application, there is provided a container door orientation detecting system comprising: a first radar mounted on the first side of the spreader, the first radar being configured to detect a first point cloud data set of the environment surrounding the first side of the container; a second radar mounted on a second side of the spreader, the second radar configured to detect a second point cloud data set of the environment surrounding the second side of the container, wherein the container door is disposed on the first side of the container or the second side of the container; the box door detection device is respectively in communication connection with the first radar and the second radar; wherein, chamber door detection device includes: the data acquisition module is respectively in communication connection with the first radar and the second radar and is used for acquiring a first point cloud data set of the surrounding environment on the first side of the container and a second point cloud data set of the surrounding environment on the second side of the container; a dispersion obtaining module, configured to obtain a first point cloud dispersion of the first point cloud data set and a second point cloud dispersion of the second point cloud data set according to the first point cloud data set and the second point cloud data set, respectively; the door determining module is used for generating information that the container door is positioned on the first side of the container when the first point cloud dispersion is greater than the second point cloud dispersion and the first point cloud dispersion is greater than a first preset value; or when the second point cloud dispersion is greater than the first point cloud dispersion and the second point cloud dispersion is greater than a first preset value, generating information that the container door is located on the second side of the container.
As a third aspect of the present application, the present application provides an electronic device including: a processor; and a memory for storing the processor executable information; the processor is used for executing the container door orientation detection method.
As a fourth aspect of the present application, there is provided a computer-readable storage medium storing a computer program for executing the container door orientation detecting method described above.
The application provides a container door orientation detection method, the radar has been adopted to detect the first point cloud data combination second point cloud data group of container both sides, and calculate the dispersion of the point cloud data of container both sides, through judging the big or small relation between the first point cloud dispersion of first point cloud data group and the second point cloud dispersion of second point cloud data group, the container side that corresponds with the point cloud dispersion height then is container door place side, thereby can snatch the container or the in-process that releases can automated inspection container door place side at the hoist, the artifical cost is reduced, the handling efficiency of container is improved.
Drawings
Fig. 1 is a schematic view illustrating an overall assembly structure of a container door orientation detecting system, a spreader and a container according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram illustrating an exemplary embodiment of a system for detecting the orientation of a door of a container;
fig. 3 is a schematic flow chart illustrating a method for detecting a door orientation of a container according to an embodiment of the present disclosure;
fig. 4 is a schematic flow chart illustrating a method for detecting a door orientation of a container according to another embodiment of the present application;
fig. 5 is a schematic flow chart illustrating a method for detecting an orientation of a door of a container according to another embodiment of the present application;
fig. 6 is a schematic flow chart illustrating a method for detecting an orientation of a door of a container according to another embodiment of the present application;
fig. 7 is a schematic flow chart illustrating a method for detecting an orientation of a door of a container according to another embodiment of the present application;
fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless explicitly specifically limited otherwise. All directional indicators in the embodiments of the present application (such as upper, lower, left, right, front, rear, top, bottom … …) are only used to explain the relative positional relationship between the components, the movement, etc. in a particular posture (as shown in the drawings), and if the particular posture is changed, the directional indicator is changed accordingly. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Furthermore, reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Fig. 1 is a schematic view of an overall structure of a container door orientation detection system, a spreader and a container according to the present invention; fig. 2 is a schematic diagram illustrating an operation of a system for detecting an orientation of a door of a container according to the present application, and fig. 3 is a schematic flowchart illustrating a method for detecting an orientation of a door of a container according to the present application.
As shown in fig. 1 and 2, the container door orientation detecting system includes: a first radar 3 and a second radar 4, and a door detection device 5, wherein the door detection device 5 is in communication with the first radar 3 and the second radar 4, respectively. Wherein the first radar 3 is installed on a first side 11 of the spreader 1, and the second radar 4 is installed on a second side 12 of the spreader 1, wherein the first side 11 and the second side 12 are opposite sides; the container 2 comprises a container first side 21 and a container second side 22, wherein the container first side 21 and the container second side 22 are opposite sides; wherein the container door 23 may be arranged at the container first side 21. Wherein the first radar 3 is configured to detect a first point cloud data set of the surroundings of the first side 21 of the container; the second radar 4 is used to detect a second point cloud data set of the surroundings of the second side 22 of the container; the door detection means 5 are arranged for detecting whether the container door is located at the first side 21 or at the second side 22 of the container based on the first point cloud data set and the second point cloud data set.
The point cloud data is a set of vectors in a three-dimensional coordinate system and is used for representing a geometric position in the three-dimensional coordinate system, and the first point cloud data group is a data group formed by a plurality of first point cloud data collected by the first radar 3 when detecting the surrounding environment of the first side 21 of the container; the second point cloud data set is a data set formed by a plurality of second point cloud data collected by the second radar 4 when detecting the surrounding environment of the second side 22 of the container.
Specifically, the door detection device 5 includes: a data acquisition module 51, configured to acquire a first point cloud data set of an ambient environment on a first side of the container and a second point cloud data set of an ambient environment on a second side of the container; the dispersion obtaining module 52 is configured to obtain a first point cloud dispersion of the first point cloud data set according to the first point cloud data set; acquiring a second point cloud dispersion of the second point cloud data set according to the second point cloud data set; the door determining module 53 is configured to generate information that the container door is located on the first side of the container when the first point cloud dispersion is greater than the second point cloud dispersion and the first point cloud dispersion is greater than a first preset value; or when the second point cloud dispersion is greater than the first point cloud dispersion and the second point cloud dispersion is greater than the first preset value, generating information that the container door is located on the second side of the container.
Specifically, the specific process of the door detection device 5 detecting whether the container door 23 is located on the first side 21 or the second side 22 of the container, i.e. the container door orientation detection method, is shown in fig. 3.
As shown in fig. 3, the container door detection method provided by the present application includes the following steps:
step S101: acquiring a first point cloud data set of the surrounding environment of a first side of the container and acquiring a second point cloud data set of the surrounding environment of a second side of the container;
the first point cloud data set of the surrounding environment of the first side of the container is the first point cloud data set in the three-dimensional area of the first side of the container.
And acquiring a second point cloud data set of the surrounding environment of the second side of the container, namely acquiring the second point cloud data set in the three-dimensional area of the second side of the container.
Step S102: respectively acquiring a first point cloud dispersion of a first point cloud data set and a second point cloud dispersion of a second point cloud data set according to the first point cloud data set and the second point cloud data set;
the first point cloud dispersion is used for reflecting indexes of difference degrees among the first point cloud data in the first point cloud data group;
the second point cloud dispersion is used for reflecting indexes of difference degree between the second point cloud data in the second point cloud data group;
step S103: judging whether the first point cloud dispersion of the first point cloud data set is larger than the second point cloud dispersion of the second point cloud data set;
when the first point cloud dispersion is greater than the second point cloud dispersion, step S104 is executed, that is:
step S104: generating information that a container door is positioned at a first side of a container;
since the door of the container is located on the first side or the second side of the container, when the determination result in step S103 is no, that is, the first point cloud dispersion is smaller than the second point cloud dispersion, step S105 is performed, that is:
step S105: information is generated that the container door is on the second side of the container.
Step S101-step S105 are that the container side corresponding to the point cloud dispersion is the container door side by judging the size relation between the first point cloud dispersion of the first point cloud data set and the second point cloud dispersion of the second point cloud data set, so that the container door side can be automatically detected in the process of grabbing or releasing the container by the lifting appliance, the manual cost is reduced, and the loading and unloading efficiency of the container is improved.
When the dispersion is used to identify the specific location side of the container door, no matter whether the container door 23 is located on the first container side 21 or the second container side 22, the first container side 21 and the second container side 22 may be provided with a handle or other member protruding outward relative to the first container side 21 or the second container side 22, and the handle or other member protruding outward relative to the first container side 21 or the second container side 22 may make the dispersion of the point cloud data set detected by the radar larger, so if only the dispersion of the point cloud data sets on the two sides of the container is used to identify the specific location side of the container door, an erroneous judgment may be generated. Therefore, the container door orientation detection system provided by the application adopts an extra preset threshold value besides the size comparison between the point cloud dispersion of the point cloud data on two sides of the container, so that the detection accuracy of the container door is improved.
Specifically, fig. 4 is a schematic flow chart of another container door orientation detection method provided in the present application, and as shown in fig. 4, between step S103 and step S104, the container door orientation detection method further includes:
step S1040: judging whether the first point cloud dispersion is greater than a first preset value, when the first point cloud dispersion is greater than the first preset value, executing step S104, namely generating information that the container door is located on the first side of the container, namely when the first point cloud dispersion is greater than the second point cloud dispersion, further detecting by adopting an additional preset threshold value, when the first point cloud dispersion is greater than the second point cloud dispersion and the first point cloud dispersion is greater than the first preset value, just generating information that the container door is located on the first side of the container, namely determining that the container door is located on the first side of the container, and further improving the accuracy of container door detection.
Similarly, between step S103 and step S105, the method for detecting the orientation of the door of the container further includes:
step S1050: and judging whether the second point cloud dispersion is greater than a first preset value, and executing the step S105 when the second point cloud dispersion is greater than the first preset value, namely generating information that the door of the container is positioned at the second side of the container.
The application provides a container door orientation detecting system when discerning the concrete position of container door according to the dispersion of the point cloud data group of the container both sides that the radar detected, has specifically adopted and has carried out the size contrast between the point cloud dispersion of the point cloud data of container both sides, has still adopted an extra threshold value of predetermineeing, has further improved the accuracy that the container door detected.
Optionally, a specific calculation manner of the dispersion of the point cloud data sets on the two sides of the container may be performed by using the following steps, and fig. 5 is a schematic flow chart of another container door orientation detection method provided in the present application, as shown in fig. 5, that is, step S102 (obtaining the first point cloud dispersion of the first point cloud data set and the second point cloud dispersion of the second point cloud data set according to the first point cloud data set and the second point cloud data set) specifically includes the following steps:
step S1021: filtering and straight line fitting are carried out on the first point cloud data group, and a first fitted straight line is generated;
step S1022: acquiring a vertical distance between each first point cloud data in the first point cloud data group and the first fitting straight line, and acquiring a first point cloud dispersion of the first point cloud data group according to the vertical distance between each first point cloud data and the first fitting straight line;
specifically, in step S1022, when the first point cloud dispersion is calculated according to the first point cloud data and the first fitted straight line, an average value method may be adopted, for example, a second average value of a vertical distance between each first point cloud data and the first fitted straight line is obtained according to a vertical distance between each first point cloud data and the first fitted straight line, that is, the first point cloud dispersion is equal to the first average value of a vertical distance between each first point cloud data and the first fitted straight line.
Step S1023: filtering and straight line fitting are carried out on the second point cloud data set, and a second fitted straight line is generated; and
step S1024: and acquiring the vertical distance between each second point cloud data in the second point cloud data set and the second fitting straight line, and acquiring the second point cloud dispersion of the second point cloud data set according to the vertical distance between each second point cloud data and the second fitting straight line.
Specifically, in step S1024, when the second point cloud dispersion is calculated according to the second point cloud data and the second fitting straight line, an average value method may be adopted, for example, a second average value of the vertical distance between each second point cloud data and the second fitting straight line is obtained according to the vertical distance between each second point cloud data and the second fitting straight line, that is, the second point cloud dispersion is equal to the second average value of the vertical distance between each second point cloud data and the second fitting straight line.
It should be understood that the calculation of the dispersion of the point cloud data sets on both sides of the container may also be calculated in other calculation manners.
When the dispersion is used to identify the specific side of the container door, no matter the container door 23 is located on the first side 21 or the second side 22, the first side 21 and the second side 22 may be provided with a handle or other member protruding outward relative to the first side 21 or the second side 22, and the handle or other member protruding outward relative to the first side 21 or the second side 22 may make the dispersion of the point cloud data set detected by the radar larger, even if one kind of container door orientation detection system adopts an additional preset threshold to improve the accuracy of the container door detection besides the size comparison between the point cloud dispersions of the point cloud data on the two sides of the container, but the accuracy is still not very high, therefore, the present application provides another kind of container door orientation detection system, besides the point cloud dispersion of the point cloud data on the two sides of the container is adopted to judge the side where the container door is located, the distance between a fitting line of the point cloud data and a standard fitting line calibrated by a radar is also adopted to judge the side where the container door is located, and the accuracy of container door detection is further improved.
Specifically, fig. 6 is a schematic flow chart of another container door orientation detection method provided in the present application, and as shown in fig. 6, between step S102 and step S103, the container door orientation detection method further includes:
step S1030: acquiring a first side box door point cloud data reference line and a second side non-box door point cloud data reference line when a standard container box door is positioned at a first side of a standard container;
step S1030 is to obtain that, when the standard container door is located on the first side of the standard container, the first side of the container is the side where the standard container door is located, and the second side of the container is the side where the standard container door is not located. At this time, the first side box door point cloud data reference line is a reference line of the box door side, and the second side non-box door point cloud data reference line is a reference line of the non-box door. That is, two reference lines are acquired in step S1030.
Step S1031: acquiring a second side box door point cloud data reference line and a first side non-box door point cloud data reference line when a standard container box door is positioned at a second side of the standard container;
similarly, step S1031 obtains that, when the standard container door is located at the second side of the standard container, the second side of the container is the side where the standard container door is located, and then the first side of the container is the side where the standard container door is not located. At this time, the second side box door point cloud data reference line is a reference line of the box door side, and the first side non-box door point cloud data reference line is a reference line of the non-box door. That is, two reference lines are acquired in step S1031.
Through step S1030 and step S1031, a total of four reference lines are obtained, which are: the first side is a first side box door point cloud data reference line when the box door is opened, the first side is a first side non-box door point cloud data reference line when the box door is not opened, the second side is a second side box door point cloud data reference line when the box door is opened, and the second side is a second side non-box door point cloud data reference line when the box door is not opened.
Between S1040 and S104, the method for detecting the orientation of the container door further includes:
step S1041: acquiring a first vertical distance between a first fitting straight line and a first side box door point cloud data reference line, and acquiring a second vertical distance between the first fitting straight line and a first side non-box door point cloud data reference line;
step S1042: and judging whether the first vertical distance is smaller than the second vertical distance, and if so, indicating that the first fitting straight line is closer to the first side box door point cloud data datum line, and executing the step S105. The container door detection method is characterized in that the container door detection method comprises the steps of judging the side of the container door by adopting point cloud dispersion of point cloud data on two sides of a container, judging the side of the container door by adopting the distance between a fitting line of the point cloud data and a calibrated standard fitting line, and further improving the detection accuracy of the container door.
Similarly, between step S1050 and step S105, the method for detecting the orientation of the door of the container further includes:
step S1051: acquiring a third vertical distance between a second fitting straight line and a second side box door point cloud data reference line, and acquiring a fourth vertical distance between the second fitting straight line and a second side non-box door point cloud data reference line;
step S1052: and judging whether the third vertical distance is smaller than the fourth vertical distance, and if so, indicating that the second fitting straight line is closer to the second side box door point cloud data datum line, and executing the step S105. The container door detection method is characterized in that the container door detection method comprises the steps of judging the side of the container door by adopting point cloud dispersion of point cloud data on two sides of a container, judging the side of the container door by adopting the distance between a fitting line of the point cloud data and a calibrated standard fitting line, and further improving the detection accuracy of the container door.
Optionally, the four reference lines (i.e., the first side box door point cloud data reference line when the first side is a box door, the first side non-box door point cloud data reference line when the first side is a non-box door, the second side box door point cloud data reference line when the second side is a box door, and the second side non-box door point cloud data reference line when the second side is a non-box door) may be obtained in the following manner.
For example, the method for acquiring the first-side box door point cloud data reference line and the second-side non-box door point cloud data reference line when the first side is the box door includes the following steps in step S1030:
(i) the method comprises the following steps When a door of a standard container is positioned at a first side of the standard container, a first reference point cloud data set of the surrounding environment of the first side of the standard container and a second reference point cloud data set of the surrounding environment of a second side of the standard container are obtained;
(ii) filtering and straight line fitting are respectively carried out on the first reference point cloud data set and the second reference point cloud data set, and a first side box door point cloud data reference line and a second side non-box door point cloud data reference line are generated;
and (ii) obtaining a first side box door point cloud data reference line and a second side non-box door point cloud data reference line when the first side is the box door.
Similarly, the method for acquiring the second side door point cloud data reference line and the first side non-door point cloud data reference line when the second side is the door, that is, the step S1031 specifically includes the following steps:
(iii) the method comprises the following steps When the door of the standard container is positioned at the second side of the standard container, a third reference point cloud data set of the surrounding environment of the first side of the standard container and a fourth reference point cloud data set of the surrounding environment of the second side of the standard container are obtained;
(iv) and respectively filtering and fitting straight lines to the third reference point cloud data group and the fourth reference point cloud data group to generate a first side non-box door point cloud data reference line and a second side box door point cloud data reference line.
And (iv) obtaining a first side non-box door point cloud data reference line and a second side box door point cloud data reference line when the second side is the box door through the steps (iii) and (iv).
In step S101, the first point cloud data set is acquired by the first radar 3, and when the first radar 3 detects the first point cloud data set in the three-dimensional space of the surrounding environment of the first side 21 of the container, because the three-dimensional space is large, the data of the irrelevant area of the first point cloud data set acquired by the first radar 3 is large, so that the data of a part of the irrelevant area exists in the first point cloud data set, the data of the irrelevant area may interfere with the detection result to some extent, and the data of the irrelevant area may increase the burden of data calculation in the detection process, therefore, in the container door detection method provided by the present application, after the door detection device 5 acquires the first point cloud data set and the second point cloud data set transmitted by the first radar 3 and the second radar 4, the first point cloud data set and the second point cloud data set need to be preprocessed first, namely, a point cloud data set in a first preset region of interest is selected from the first point cloud data set, and a first effective point cloud data set is generated. And selecting point cloud data in a second preset region of interest from the second point cloud data set to generate a second effective point cloud data set.
Specifically, fig. 7 is a schematic flow chart of the method for detecting the orientation of the container door according to the present invention, and as shown in fig. 7, between step S101 and step S102, the method for detecting the container door further includes:
step S106: extracting a point cloud data set in a first preset region of interest from the first point cloud data set to generate a first effective point cloud data set;
step S107: extracting a point cloud data set in a second preset interest area from the second point cloud data set to generate a second effective point cloud data set;
in this case, the step S102 (obtaining the first point cloud dispersion of the first point cloud data set and the second point cloud dispersion of the second point cloud data set according to the first point cloud data set and the second point cloud data set respectively) includes:
and respectively acquiring the first point cloud dispersion of the first point cloud data set and the second point cloud dispersion of the second point cloud data set according to the first effective point cloud data set and the second effective point cloud data set.
According to the container door orientation detection method, after the first point cloud data group and the second point cloud data group detected by the first radar 3 and the second radar 4 are obtained, the point cloud data in the preset area is extracted from the first point cloud data group and the second point cloud data group, the first effective point cloud data group and the second effective point cloud data group are generated, then the container door side is detected according to the first effective point cloud data group and the second effective point cloud data group, the detection precision is further improved, and the calculation burden of the data is reduced.
Next, an electronic apparatus according to an embodiment of the present application is described with reference to fig. 8. As shown in fig. 8, the electronic device 600 includes one or more processors 601 and memory 602.
The processor 601 may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or information execution capabilities, and may control other components in the electronic device 600 to perform desired functions.
Memory 601 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, Random Access Memory (RAM), cache memory (cache), and/or the like. The non-volatile memory may include, for example, Read Only Memory (ROM), hard disk, flash memory, etc. One or more computer program information may be stored on the computer readable storage medium and executed by the processor 601 to implement the container door orientation detection methods of the various embodiments of the present application described above or other desired functions.
In one example, the electronic device 600 may further include: an input device 603 and an output device 604, which are interconnected by a bus system and/or other form of connection mechanism (not shown).
The input device 603 may include, for example, a keyboard, a mouse, and the like.
The output device 604 can output various kinds of information to the outside. The output means 604 may comprise, for example, a display, a communication network, a remote output device connected thereto, and the like.
Of course, for simplicity, only some of the components of the electronic device 600 relevant to the present application are shown in fig. 8, and components such as buses, input/output interfaces, and the like are omitted. In addition, electronic device 600 may include any other suitable components depending on the particular application.
In addition to the above-described methods and apparatus, embodiments of the present application may also be a computer program product comprising computer program information which, when executed by a processor, causes the processor to perform the steps in the container door orientation detection methods according to various embodiments of the present application described in the present specification.
The computer program product may be written with program code for performing the operations of embodiments of the present application in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, embodiments of the present application may also be a computer-readable storage medium having stored thereon computer program information which, when executed by a processor, causes the processor to perform the steps of the present description in a container door orientation detection method according to various embodiments of the present application.
The computer-readable storage medium may take any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may include, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The foregoing describes the general principles of the present application in conjunction with specific embodiments, however, it is noted that the advantages, effects, etc. mentioned in the present application are merely examples and are not limiting, and they should not be considered essential to the various embodiments of the present application. Furthermore, the foregoing disclosure of specific details is for the purpose of illustration and description and is not intended to be limiting, since the foregoing disclosure is not intended to be exhaustive or to limit the disclosure to the precise details disclosed.
The block diagrams of devices, apparatuses, systems referred to in this application are only given as illustrative examples and are not intended to require or imply that the connections, arrangements, configurations, etc. must be made in the manner shown in the block diagrams. These devices, apparatuses, devices, systems may be connected, arranged, configured in any manner, as will be appreciated by those skilled in the art. Words such as "including," "comprising," "having," and the like are open-ended words that mean "including, but not limited to," and are used interchangeably therewith. The words "or" and "as used herein mean, and are used interchangeably with, the word" and/or, "unless the context clearly dictates otherwise. The word "such as" is used herein to mean, and is used interchangeably with, the phrase "such as but not limited to".
It should also be noted that in the devices, apparatuses, and methods of the present application, the components or steps may be decomposed and/or recombined. These decompositions and/or recombinations are to be considered as equivalents of the present application.
The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the application. Thus, the present application is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the present invention, and any modifications, equivalents and the like that are within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method of detecting a door orientation of a container, comprising:
acquiring a first point cloud data set of the surrounding environment of a first side of a container and a second point cloud data set of the surrounding environment of a second side of the container, wherein a container door is arranged on the first side of the container or the second side of the container;
respectively acquiring a first point cloud dispersion of the first point cloud data set and a second point cloud dispersion of the second point cloud data set according to the first point cloud data set and the second point cloud data set;
when the first point cloud dispersion is larger than the second point cloud dispersion, generating information that the container door is positioned at the first side of the container;
and when the second point cloud dispersion is greater than the first point cloud dispersion, generating information that the container door is positioned at the second side of the container.
2. The method of claim 1, wherein generating information that the container door is located on the first side of the container when the first point cloud dispersion is greater than the second point cloud dispersion comprises:
when the first point cloud dispersion is larger than the second point cloud dispersion and the first point cloud dispersion is larger than a first preset value, generating information that the container door is positioned at the first side of the container;
when the second point cloud dispersion is greater than the first point cloud dispersion, generating information that the container door is located at the second side of the container, including:
and when the second point cloud dispersion is greater than the first point cloud dispersion and the second point cloud dispersion is greater than the first preset value, generating information that the container door is located on the second side of the container.
3. The method for detecting the orientation of a door of a container according to claim 1, wherein obtaining the first point cloud dispersion of the first point cloud data set and the second point cloud dispersion of the second point cloud data set from the first point cloud data set and the second point cloud data set, respectively, comprises:
filtering and straight line fitting are carried out on the first point cloud data group, and a first fitted straight line is generated;
acquiring a vertical distance between each first point cloud data in the first point cloud data group and the first fitting straight line, and acquiring a first point cloud dispersion of the first point cloud data group according to the vertical distance between each first point cloud data and the first fitting straight line;
filtering and straight line fitting are carried out on the second point cloud data group, and a second fitted straight line is generated; and
and acquiring the vertical distance between each second point cloud data in the second point cloud data set and the second fitting straight line, and acquiring the second point cloud dispersion of the second point cloud data set according to the vertical distance between each second point cloud data and the second fitting straight line.
4. The method according to claim 3, wherein after obtaining the first point cloud dispersion of the first point cloud data set and the second point cloud dispersion of the second point cloud data set from the first point cloud data set and the second point cloud data set, respectively, the method further comprises:
acquiring a first-side box door point cloud data reference line and a second-side non-box door point cloud data reference line when a box door of a standard container is positioned at a first side of the standard container;
acquiring a point cloud data reference line of a door of a second side door and a point cloud data reference line of a non-door of a first side when the door of the standard container is positioned at the second side of the standard container;
wherein, when the first point cloud dispersion is greater than the second point cloud dispersion, generating information that the container door is located at the first side of the container further comprises:
when the first point cloud dispersion is larger than the second point cloud dispersion, and the vertical distance between the first fitting straight line and the first side door point cloud data reference line is smaller than the vertical distance between the first fitting straight line and the first side non-door point cloud data reference line, generating information that the container door is positioned at the first side of the container;
when the second point cloud dispersion is greater than the first point cloud dispersion, generating information that the container door is located at the second side of the container, including:
and when the second point cloud dispersion is greater than the first point cloud dispersion and the vertical distance between the second fitting straight line and the second side door point cloud data reference line is smaller than the vertical distance between the second fitting straight line and the second side non-door point cloud data reference line, generating information that the container door is positioned at the second side of the container.
5. The method of detecting the orientation of a door of a container according to claim 4,
acquiring a first side box door point cloud data reference line and a second side non-box door point cloud data reference line when a standard container box door is positioned on a first side of a standard container, and the method comprises the following steps:
when a door of a standard container is positioned at a first side of the standard container, acquiring a first reference point cloud data set of the surrounding environment of the first side of the standard container and a second reference point cloud data set of the surrounding environment of a second side of the standard container; and
filtering and straight line fitting are respectively carried out on the first reference point cloud data set and the second reference point cloud data set, and a first side box door point cloud data reference line and a second side non-box door point cloud data reference line are generated;
acquiring a first side non-container door point cloud data reference line and a second side container door point cloud data reference line when a standard container door is positioned on a second side of the standard container, wherein the acquiring comprises the following steps:
when a door of a standard container is positioned at a second side of the standard container, a third reference point cloud data set of the surrounding environment of the second side of the standard container and a fourth reference point cloud data set of the surrounding environment of the first side of the standard container are obtained; and
and respectively filtering and fitting straight lines to the third reference point cloud data group and the fourth reference point cloud data group to generate a second side box door point cloud data reference line and a first side non-box door point cloud data reference line.
6. The method of detecting the orientation of a door of a container according to claim 3,
obtaining a first point cloud dispersion of the first point cloud data group according to a vertical distance between each first point cloud data and the first fitting straight line, including:
according to the vertical distance between each first point cloud data and the first fitting straight line, obtaining a first average value of the vertical distance between each first point cloud data and the first fitting straight line; wherein the first point cloud dispersion comprises the first average;
acquiring second point cloud dispersion of the second point cloud data set according to the vertical distance between each second point cloud data and the second fitting straight line, wherein the second point cloud dispersion comprises:
acquiring a second average value of the vertical distance between each second point cloud data and the second fitting straight line according to the vertical distance between each second point cloud data and the second fitting straight line; wherein the second point cloud dispersion comprises the second average.
7. The method of claim 1, wherein after acquiring the first point cloud data set of the environment around the first side of the container and the second point cloud data set of the environment around the second side of the container, and before acquiring the first point cloud dispersion of the first point cloud data set and the second point cloud dispersion of the second point cloud data set from the first point cloud data set and the second point cloud data set, respectively, the method further comprises:
extracting a point cloud data set in a first preset region of interest from the first point cloud data set to generate a first effective point cloud data set;
extracting a point cloud data set in a second preset interest area from the second point cloud data set to generate a second effective point cloud data set;
wherein obtaining a first point cloud dispersion of the first point cloud data set according to the first point cloud data set comprises: acquiring a first point cloud dispersion of the first effective point cloud data set according to the first effective point cloud data set;
obtaining a second point cloud dispersion of the second point cloud data set according to the second point cloud data set comprises: and acquiring second point cloud dispersion of the second effective point cloud data set according to the second effective point cloud data set.
8. A container door orientation detection system, comprising:
a first radar mounted on the first side of the spreader, the first radar being configured to detect a first point cloud data set of the environment surrounding the first side of the container;
a second radar mounted on a second side of the spreader, the second radar configured to detect a second point cloud data set of the environment surrounding the second side of the container, wherein the container door is disposed on the first side of the container or the second side of the container; and
the box door detection device is respectively in communication connection with the first radar and the second radar;
wherein, chamber door detection device includes:
the data acquisition module is respectively in communication connection with the first radar and the second radar and is used for acquiring a first point cloud data set of the surrounding environment on the first side of the container and a second point cloud data set of the surrounding environment on the second side of the container;
a dispersion obtaining module, configured to obtain a first point cloud dispersion of the first point cloud data set and a second point cloud dispersion of the second point cloud data set according to the first point cloud data set and the second point cloud data set, respectively;
the door determining module is used for generating information that the container door is positioned on the first side of the container when the first point cloud dispersion is greater than the second point cloud dispersion and the first point cloud dispersion is greater than a first preset value; or when the second point cloud dispersion is greater than the first point cloud dispersion and the second point cloud dispersion is greater than a first preset value, generating information that the container door is located on the second side of the container.
9. An electronic device, characterized in that the electronic device comprises:
a processor; and
a memory for storing the processor executable information;
wherein the processor is configured to execute the method for detecting the orientation of the door of the container as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that the storage medium stores a computer program for executing the method of detecting the orientation of a container door according to any one of claims 1 to 7.
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