A Downhole Obstacle Detection Method and Device Based on Multi-Line Radar

Abstract

The present application discloses a method and device for detecting underground obstacles based on a multi-line radar, including: obtaining point cloud data of the multi-line radar and single-line radar data of the multi-line radar in the horizontal direction; taking the connection lines between the position points on the side walls on the same side of two fixed-angle radar lines on both sides of the moving object's advancing direction in the single-line radar data, and determining whether the angle difference between the above connection lines at the current moment and the previous moment is less than a preset threshold, so as to determine whether it is a straight road or a curved road area at the current time, and dynamically adjust the size of the region of interest; avoiding the intersection of the region of interest with the roadway wall, triggering no detection of obstacles and causing unnecessary parking; obtaining obstacle information based on the point cloud data within the region of interest. Through the multi-line lidar in the present invention, high-precision three-dimensional measurement can be achieved, the detection distance is far, and it is not affected by the light conditions in the coal mine underground.

Description

Technical Field

[0001] This application relates to obstacle detection, in particular to a method and device for detecting underground obstacles based on a multi-line radar. Background Art

[0002] The mine environment has a high risk factor and poor lighting conditions. Locomotives, staff, objects, etc. all need to pass through the roadway, and the roadway space is limited. Therefore, higher requirements are put forward for the driving safety of mine locomotives.

[0003] Sensors such as ultrasonic, millimeter-wave radar, and cameras all have obvious defects when used in the mine environment. For example, the method based on ultrasonic detection is planar detection and the distance is relatively short. The obstacle detection based on millimeter-wave radar is only sensitive to moving objects or metallic objects. And the method based on machine vision is easily affected by light and the detection distance is relatively short. Summary of the Invention

[0004] Embodiments of this application provide a method and device for detecting underground obstacles based on a multi-line radar to at least solve the technical problem of difficult underground obstacle detection.

[0005] According to one aspect of this application, a method for detecting underground obstacles based on a multi-line radar is provided, including:

[0006] Obtain the point cloud data of the multi-line radar and the single-line radar data of the multi-line radar in the horizontal direction, where the multi-line radar is arranged at the end of the underground moving object in the moving direction;

[0007] Take the connection line between the position points on the side wall of the same side of each two fixed-angle radar lines on both sides of the moving object's forward direction in the single-line radar data, and judge whether the angle difference between the connection lines at the current moment and the previous moment is less than a preset threshold. When it is less than the preset threshold, set the region of interest in the point cloud data of the multi-line radar as the region composed of a range with a preset length D1 along the first direction starting from the cross-section of the end of the moving object, where the first direction is perpendicular to the cross-section; otherwise, set the region of interest in the point cloud data of the multi-line radar as the region composed of a range with a preset length D2 along the second direction starting from the cross-section of the end of the moving object, where the second direction is the angular bisector direction of the angle formed by the angular bisectors of the two fixed-angle radar lines on the same side at the current moment and the angular bisectors of the two fixed-angle radar lines on the opposite side; D2 is less than D1;

[0008] Obtain obstacle information based on the point cloud data in the region of interest.

[0009] Further, before obtaining the point cloud data of the multi-line radar and the single-line radar data of the multi-line radar in the horizontal direction, it further includes:

[0010] Obtain the moving direction of the moving object, and activate the multi-line radar at one end in the moving direction.

[0011] Further, the preset length D1 and the preset length D2 are proportional to the current moving speed of the moving object.

[0012] Further, after determining whether the angle difference between the above-mentioned connection lines at the current moment and the previous moment is less than a preset threshold, it further includes: when it is greater than the preset value, reduce the moving speed of the moving object, and the reduction ratio of the moving speed is proportional to the angle difference between the above-mentioned connection lines at the current moment and the previous moment.

[0013] Further, after determining whether the angle difference between the above-mentioned connection lines at the current moment and the previous moment is less than a preset threshold, it further includes: when it is less than the preset value, increase the moving speed of the moving object to below the speed limit.

[0014] Another aspect of the present application is to provide an underground obstacle detection device based on a multi-line radar, including

[0015] A radar data acquisition module, configured to acquire the point cloud data of the multi-line radar and the single-line radar data in the horizontal direction in the multi-line radar, and the multi-line radar is arranged at the end of the underground moving object in the moving direction;

[0016] A judgment and setting module, configured to take the connection lines between the position points on the side walls of two fixed-angle radar lines on both sides of the moving direction of the single-line radar data, and judge whether the angle difference between the above-mentioned connection lines at the current moment and the previous moment is less than a preset threshold. When it is less than the preset threshold, set the region of interest in the point cloud data of the multi-line radar as a region composed of a range with a preset length D1 along a first direction starting from the cross-section at the end of the moving object, and the first direction is perpendicular to the cross-section; otherwise, set the region of interest in the point cloud data of the multi-line radar as a region composed of a range with a preset length D2 along a second direction starting from the cross-section at the end of the moving object, and the second direction is the angular bisector direction of the angle formed by the angular bisectors of the two fixed-angle radar lines on the same side at the current moment and the angular bisectors of the two fixed-angle radar lines on the opposite side; D2 is less than D1;

[0017] An obstacle information acquisition module, configured to obtain obstacle information based on the point cloud data in the region of interest.

[0018] Further, the radar data acquisition module is further configured to: before acquiring the point cloud data of the multi-line radar and the single-line radar data in the horizontal direction in the multi-line radar, acquire the moving direction of the moving object, and activate the multi-line radar at one end in the moving direction.

[0019] Further, the determination and setting module is further configured to: after determining whether the angle difference between the current moment and the previous moment of the above connection line is less than a preset threshold, further include: when it is greater than the preset value, reducing the moving speed of the moving object, and the reduction ratio of the moving speed is proportional to the angle difference between the current moment and the previous moment of the above connection line.

[0020] According to another aspect of the present application, there is also provided a processor for executing software, and the software is used to execute the method described above.

[0021] According to another aspect of the present application, there is also provided a memory for storing software, and the software is used to execute the method described above.

[0022] In the method of the present invention, high-precision three-dimensional measurement can be achieved based on a multi-line lidar, the detection distance is far, and it is not affected by the light conditions in the coal mine. The straight roadway and the curved roadway are sensed by the lidar. While realizing the three-dimensional detection of moving and static obstacles, the detection of the roadway curve is supplemented to realize that the locomotive automatically changes the detection area when going straight and turning in the roadway to adapt to the roadway environment scene. Due to the setting of the region of interest, the algorithm can run on low-power and low-configuration embedded devices and can ensure a detection frequency same as the lidar data frequency, achieving good detection results under the limited hardware conditions in the mine. Therefore, it is particularly suitable for the mine roadway environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings constituting a part of this application are used to provide a further understanding of this application. The schematic embodiments of this application and their descriptions are used to explain this application and do not constitute an improper limitation to this application. In the drawings:

[0024] Figure 1 is a flowchart of a method for detecting underground obstacles based on a multi-line radar according to an embodiment of the present application;

[0025] Figure 2 is a schematic diagram of radar lines when in the straight part underground according to an embodiment of the present application;

[0026] Figure 3 is a schematic diagram of radar lines when in the turning part underground according to an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] It should be noted that, without conflict, the embodiments in this application and the features in the embodiments can be combined with each other. The following will refer to the drawings and combine the embodiments to detail this application.

[0028] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0029] As Figure 1 is a flowchart of a method for detecting underground obstacles based on a multi-line radar according to an embodiment of the present application. As Figure 1 shown, the process includes the following steps:

[0030] Step S102: Obtain the point cloud data of the multi-line radar and the single-line radar data of the multi-line radar in the horizontal direction. The multi-line radar is arranged at the end of the underground moving object in the moving direction;

[0031] Step S104: Take the connection line between the position points on the side wall of the same side of each two fixed-angle radar lines on both sides of the moving object's forward direction in the single-line radar data, and judge whether the angle difference between the connection lines at the current moment and the previous moment is less than a preset threshold. When it is less than the preset threshold, set the region of interest in the point cloud data of the multi-line radar as the region composed of a range with a preset length D1 along the first direction starting from the cross-section of the end of the moving object, and the first direction is perpendicular to the cross-section; otherwise, set the region of interest in the point cloud data of the multi-line radar as the region composed of a range with a preset length D2 along the second direction starting from the cross-section of the end of the moving object, and the second direction is the angular bisector direction of the angle formed by the angular bisectors of the two fixed-angle radar lines on the same side at the current moment and the angular bisectors of the two fixed-angle radar lines on the opposite side; D2 is less than D1;

[0032] Step S106: Obtain obstacle information based on the point cloud data in the region of interest.

[0033] By using the above method, it can run on an embedded device. At the same time, the detection speed is the same as the frame rate of the lidar, reducing the platform cost and power consumption; the obstacle detection based on the multi-line lidar sensor is not affected by the light in the mine roadway, and can realize the obstacle detection in the three-dimensional region composed of the cross-section of the locomotive and the distance ahead, with strong applicability; taking single-line data from the multi-line lidar data for curve detection, judging whether the angle difference is greater than the preset threshold to realize curve judgment, and further realizing the adaptive change of the detection region for straight roadways and curve roadways. Taking single-line lidar data can reduce the requirement for hardware computing power, ensure the detection rate, and realize the reuse of sensor data.

[0034] As Figure 2The figure shows a schematic diagram of the radar line when it is in the straight section underground. When the mine locomotive is in this area, the track is usually laid straight. The detection angles of the same radar line on the mine wall at adjacent moments are almost unchanged. Therefore, it can be judged that the roadway here is a straight roadway. The safety of a straight roadway is inherently higher than that of the turning section under the same conditions. Therefore, a longer region of interest can be set for the mine locomotive. As Figure 3 The figure shows a schematic diagram of the radar line when it is in the turning section underground. In the actual implementation process, the single-line lidar data needs to be converted from the polar coordinate system to the rectangular coordinate system. The figure shows the detection lines of a single-line radar in a certain horizontal direction on both sides of the mine wall at the same moment. Connect the two points on the same side among the position points of the radar lines on the left and right roadway walls on the side wall respectively. This connection reflects the approximate trend of the roadway wall near this position. If the angle difference between the connections on the same side at two adjacent moments is large, that is, the change of the connection is large, it can reflect that the change of the roadway wall is large. Because the roadway wall is not smooth, the slope will change within a threshold. When in a curve, the slope between two points on the fixed angle of the sensor hitting the roadway wall will increase significantly, and the difference from the previous moment is large. Thus, it is judged that the curve is entered. After entering the curve, since the obstacles at the outer lane of the turn are more likely to collide with the vehicle body, the direction of line O in the figure is further selected, that is, the angular bisector direction of O1 and O2. Among them, O1 is the angular bisector of the lidar at adjacent moments on the left side, and O2 is the angular bisector of the lidar at adjacent moments on the right side. The direction of line O selected by the above method points to the outer lane of the turn, and can detect obstacles more effectively.

[0035] Preferably, lidar is installed at both ends of a moving object such as a mine locomotive. In this embodiment, a 16-line lidar is selected, and the radar at different positions is selected according to the up and down running states of the mine locomotive. Therefore, before obtaining the point cloud data of the multi-line radar and the single-line radar data of the multi-line radar in the horizontal direction, it also includes: obtaining the moving direction of the moving object and starting the multi-line radar at one end in the moving direction. Through the above data switching, the method in this embodiment is applicable to both the up and down running directions of the mine locomotive.

[0036] Preferably, since the faster the speed, the more distant areas need to be detected for obstacles in order to leave enough deceleration areas. Therefore, the preset lengths D1 and D2 are proportional to the current moving speed of the moving object.

[0037] Preferably, after judging whether the angle difference between the above connections at the current moment and the previous moment is less than the preset threshold, it also includes: when it is greater than the preset value, reducing the moving speed of the moving object, and the reduction ratio of the moving speed is proportional to the angle difference between the above connections at the current moment and the previous moment. In this way, the driving safety in the turning area is improved by decelerating.

[0038] Preferably, after determining whether the angle difference between the current moment and the previous moment of the above connection line is less than a preset threshold, the method further includes: when it is less than the preset value, increasing the moving speed of the moving object to below the speed limit. In this way, the operation efficiency in a relatively safe straight area is improved by accelerating.

[0039] As an alternative embodiment, to realize the perception of the roadway environment and the detection of obstacles in the roadway, the specific steps are as follows: First, take out the target point cloud data from the shared memory; Second, in order to detect smaller obstacles, the target point cloud data is segmented according to the distance. The purpose is that the clustering radius increases continuously from near to far according to the segmentation. After performing Euclidean clustering on the target frame point cloud data, N (N>=0) sub-point cloud regions of the detected obstacles are generated. For each of the N sub-point cloud regions generated in the previous step, an external cube fitting process is performed to calculate the center point coordinates (x, y, z), side lengths (l, w, h), distance, angle, volume, etc. from the sub-point cloud region to the center point of the lidar. Finally, the obstacles are sorted according to the distance, and the information of the obstacle closest to the locomotive is taken.

[0040] The specific steps of obstacle detection in the above steps are as follows: First, take out the cloud data of the region of interest; Second, in order to detect smaller obstacles, the target point cloud data is segmented according to the distance. The purpose is that the clustering radius increases continuously from near to far according to the segmentation. After performing Euclidean clustering on the target frame point cloud data, N (N>=0) sub-point cloud regions of the detected obstacles are generated. For each of the N sub-point cloud regions generated in the previous step, an external cube fitting process is performed to calculate the center point coordinates (x, y, z), side lengths (l, w, h), distance, angle, volume, etc. from the sub-point cloud region to the center point of the lidar. Finally, the obstacles are sorted according to the distance, and the information of the obstacle closest to the locomotive is taken.

[0041] In this embodiment, an electronic device is provided, including a memory and a processor. A computer program is stored in the memory, and the processor is configured to run the computer program to execute the method in the above embodiments.

[0042] These computer programs can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate computer-implemented processing. Thus, the instructions executed on the computer or other programmable device provide for realizing in the process Figure 1 a process or multiple processes and / or blocks Figure 1Steps of functions specified in one or more boxes can be implemented by different modules corresponding to different steps. In this case, the computer program can also be referred to as an underground obstacle detection device based on a multi-line radar, including: a radar data acquisition module for acquiring point cloud data of the multi-line radar and single-line radar data of the multi-line radar in the horizontal direction, where the multi-line radar is arranged at the end of the underground moving object in the moving direction; a judgment and setting module for taking the connection line between the position points on the side wall on the same side of two fixed-angle radar lines on both sides of the single-line radar data in the forward direction of the moving object, and judging whether the angle difference between the connection lines at the current moment and the previous moment is less than a preset threshold. When it is less than the preset threshold, the region of interest in the point cloud data of the multi-line radar is set as a region composed of a range with a preset length D1 along a first direction starting from the cross-section at the end of the moving object, and the first direction is perpendicular to the cross-section; otherwise, the region of interest in the point cloud data of the multi-line radar is set as a region composed of a range with a preset length D2 along a second direction starting from the cross-section at the end of the moving object, and the second direction is the angular bisector direction of the angle formed by the angular bisectors of two fixed-angle radar lines on the same side at the current moment and the angular bisectors of two fixed-angle radar lines on the opposite side; D2 is less than D1; an obstacle information acquisition module for obtaining obstacle information based on the point cloud data in the region of interest.

[0043] The above computer program solves the problem of difficult obstacle detection in the mine roadway environment, making the implementation of underground obstacle detection highly feasible.

[0044] Preferably, the radar data acquisition module is further configured to:

[0045] Before acquiring the point cloud data of the multi-line radar and the single-line radar data of the multi-line radar in the horizontal direction,

[0046] acquire the moving direction of the moving object and start the multi-line radar at one end in the moving direction.

[0047] Preferably, the judgment and setting module is further configured to: after judging whether the angle difference between the connection lines at the current moment and the previous moment is less than the preset threshold, it further includes: when it is greater than the preset value, reduce the moving speed of the moving object, and the reduction ratio of the moving speed is proportional to the angle difference between the connection lines at the current moment and the previous moment.

[0048] The above program can run in a processor or can also be stored in a memory (or referred to as a computer-readable medium). A computer-readable medium includes permanent and non-permanent, removable and non-removable media and can implement information storage by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer-readable medium does not include transitory media such as modulated data signals and carrier waves.

[0049] The above are only embodiments of the present application and are not used to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A downhole obstacle detection method based on multi-line radar, characterized in that: Including: Obtaining the point cloud data of a multi-line radar and the single-line radar data of the multi-line radar in the horizontal direction, where the multi-line radar is arranged at the end of an underground moving object in the moving direction; Taking the connection lines between the position points on the side wall on the same side of two fixed-angle radar lines on both sides of the moving object's forward direction in the single-line radar data, and determining whether the angle difference between the current moment and the previous moment of these connection lines is less than a preset threshold; When it is less than the preset threshold, setting the region of interest in the point cloud data of the multi-line radar as the region composed of a range with a preset length D1 along a first direction starting from the cross-section at the end of the moving object, where the first direction is perpendicular to the cross-section; otherwise, setting the region of interest in the point cloud data of the multi-line radar as the region composed of a range with a preset length D2 along a second direction starting from the cross-section at the end of the moving object, where the second direction is the angular bisector direction of the angle formed by the angular bisectors of two fixed-angle radar lines on the same side at the current moment and the angular bisectors of two fixed-angle radar lines on the opposite side; D2 is less than D1; Obtaining obstacle information based on the point cloud data within the region of interest.

2. The method according to claim 1, wherein: Before obtaining the point cloud data of the multi-line radar and the single-line radar data of the multi-line radar in the horizontal direction, it further includes: Obtaining the moving direction of the moving object and starting the multi-line radar at one end in the moving direction.

3. The method according to claim 1, wherein: The preset length D1 and the preset length D2 are proportional to the current moving speed of the moving object.

4. The method according to claim 3, wherein: After determining whether the angle difference between the current moment and the previous moment of the above connection lines is less than the preset threshold, it further includes: When it is greater than the preset value, reducing the moving speed of the moving object, and the reduction ratio of the moving speed is proportional to the angle difference between the current moment and the previous moment of the above connection lines.

5. The method according to claim 4, wherein: After determining whether the angle difference between the current moment and the previous moment of the above connection lines is less than the preset threshold, it further includes: When it is less than the preset value, increasing the moving speed of the moving object to below the speed limit.

6. An underground obstacle detection device based on multi-line radar, characterized in that: Including: A radar data acquisition module for obtaining the point cloud data of a multi-line radar and the single-line radar data of the multi-line radar in the horizontal direction, where the multi-line radar is arranged at the end of an underground moving object in the moving direction; A judgment and setting module, configured to obtain the connection line between the position points on the side walls on the same side of two fixed-angle radar lines on both sides of the moving object's forward direction from the single-line radar data, and judge whether the angle difference between the above connection lines at the current moment and the previous moment is less than a preset threshold. When it is less than the preset threshold, set the region of interest in the point cloud data of the multi-line radar as the region composed of a range with a preset length D1 along a first direction starting from the cross-section at the end of the moving object, and the first direction is perpendicular to the cross-section; otherwise, set the region of interest in the point cloud data of the multi-line radar as the region composed of a range with a preset length D2 along a second direction starting from the cross-section at the end of the moving object, and the second direction is the angular bisector direction of the angle formed by the angular bisectors of two fixed-angle radar lines on the same side at the current moment and the angular bisectors of two fixed-angle radar lines on the opposite side; D2 is less than D1. An obstacle information acquisition module, configured to obtain obstacle information based on the point cloud data in the region of interest.

7. The device according to claim 6, characterized in that: The radar data acquisition module is further configured to: Before acquiring the point cloud data of the multi-line radar and the single-line radar data of the multi-line radar in the horizontal direction, acquire the moving direction of the moving object and activate the multi-line radar at one end in the moving direction.

8. The device according to claim 6, characterized in that: The judgment and setting module is further configured to: After judging whether the angle difference between the above connection lines at the current moment and the previous moment is less than the preset threshold, it further includes: when it is greater than the preset value, reduce the moving speed of the moving object, and the reduction ratio of the moving speed is proportional to the angle difference between the above connection lines at the current moment and the previous moment.

9. A processor for executing a computer program, characterized in that, The computer program is used to execute the method according to any one of claims 1 to 5.

10. A memory for storing a computer program, characterized in that, The computer program is used to execute the method according to any one of claims 1 to 5.

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