CN110133624B - Unmanned driving abnormity detection method, device, equipment and medium - Google Patents

Unmanned driving abnormity detection method, device, equipment and medium Download PDF

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CN110133624B
CN110133624B CN201910398311.0A CN201910398311A CN110133624B CN 110133624 B CN110133624 B CN 110133624B CN 201910398311 A CN201910398311 A CN 201910398311A CN 110133624 B CN110133624 B CN 110133624B
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CN110133624A (en
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殷其娟
张磊
张伍召
王晓艳
陈卓
王柏生
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Apollo Intelligent Technology Beijing Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/40—Means for monitoring or calibrating
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/497—Means for monitoring or calibrating

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Abstract

The embodiment of the invention discloses a method, a device, equipment and a medium for detecting unmanned driving abnormity, and relates to the field of unmanned driving. The method comprises the following steps: determining the farthest detection distance of the sensor to be detected and the projection position of a position point positioned at the farthest detection distance in the sensing data according to the sensing data of the sensor to be detected; and determining whether the detection range of the sensor to be detected is abnormal or not according to the farthest detection distance of the sensor to be detected and the projection position of the position point positioned at the farthest detection distance. The unmanned driving abnormity detection method, the unmanned driving abnormity detection device, the unmanned driving abnormity detection equipment and the unmanned driving abnormity detection medium, provided by the embodiment of the invention, realize abnormity detection on the detection range of the lidar.

Description

Unmanned driving abnormity detection method, device, equipment and medium
Technical Field
The embodiment of the invention relates to the field of unmanned driving, in particular to an unmanned driving abnormity detection method, device, equipment and medium.
Background
The unmanned driving senses the surrounding environment of the vehicle by using a vehicle-mounted sensor, and controls the steering and the speed of the vehicle according to the road, the vehicle position and the obstacle information obtained by sensing, so that the vehicle can safely and reliably run on the road.
In unmanned systems, lidar sensors (lidar) are important for positioning, sensing, etc. modules. If the maximum detection range of the lidar is reduced due to insufficient power and the like, the distance for the lidar to detect the obstacle may be reduced, so that the detection result of the sensing module is influenced, and finally, the whole automatic driving strategy is influenced.
Disclosure of Invention
The embodiment of the invention provides a method, a device, equipment and a medium for detecting unmanned abnormal conditions, which are used for realizing abnormal detection of a lidar detection range.
In a first aspect, an embodiment of the present invention provides an anomaly detection method, where the method includes:
determining the farthest detection distance of the sensor to be detected and the projection position of a position point positioned at the farthest detection distance in the sensing data according to the sensing data of the sensor to be detected;
and determining whether the detection range of the sensor to be detected is abnormal or not according to the farthest detection distance of the sensor to be detected and the projection position of the position point positioned at the farthest detection distance.
Further, the determining the farthest detection distance of the sensor to be detected according to the sensing data of the sensor to be detected includes:
determining the distance between each position point in the sensing data and the sensor to be detected according to the three-dimensional space characteristic data of each position point in the sensing data of the sensor to be detected;
and taking the maximum value of the distances as the farthest detection distance.
Further, the determining, according to sensing data of a sensor to be detected, a projection position of a position point located at the farthest detection distance determined by three-dimensional space feature data in the sensing data includes:
and if the height of the position point at the farthest detection distance is determined to be smaller than a set height threshold value according to the three-dimensional space characteristic data of the position point in the sensing data, determining that the projection position of the position point is the ground.
Further, the determining whether the detection range of the sensor to be detected is abnormal according to the farthest detection distance of the sensor to be detected and the projection position of the position point located at the farthest detection distance includes:
if the farthest detection distance of the sensor to be detected is smaller than a set distance threshold value, and the projection position of the position point which is larger than the set number threshold value in the position points at the farthest detection distance is the ground, determining the sensing data as detection range reduction data;
and if the number of times of continuously monitoring the reduction data of the detection range is larger than a set number threshold, determining that the detection range of the sensor to be detected is reduced.
In a second aspect, an embodiment of the present invention further provides an abnormality detection apparatus, including:
the data determination module is used for determining the farthest detection distance of the sensor to be detected and the projection position of a position point positioned at the farthest detection distance in the sensing data according to the sensing data of the sensor to be detected;
and the abnormality detection module is used for determining whether the detection range of the sensor to be detected is abnormal or not according to the farthest detection distance of the sensor to be detected and the projection position of the position point positioned at the farthest detection distance.
Further, the data determination module includes:
the distance determining unit is used for determining the distance between each position point in the sensing data and the sensor to be detected according to the three-dimensional space characteristic data of each position point in the sensing data of the sensor to be detected;
a farthest distance determination unit configured to take a maximum value of the distances as a farthest detection distance.
Further, the data determination module includes:
and the projection position determining unit is used for determining that the projection position of the position point is the ground if the height of the position point located at the farthest detection distance is determined to be smaller than a set height threshold value according to the three-dimensional space characteristic data in the sensing data position point.
Further, the anomaly detection module includes:
the reduced data determining unit is used for determining the sensing data as reduced detection range data if the farthest detection distance of the sensor to be detected is smaller than a set distance threshold value and the projection position of the position point which is larger than the set number threshold value in the position points at the farthest detection distance is the ground;
and the range reduction determining unit is used for determining that the detection range of the sensor to be detected is reduced if the number of times of continuously monitoring the detection range reduction data is greater than a set number threshold.
In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement an anomaly detection method as described in any embodiment of the invention.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the abnormality detection method according to any one of the embodiments of the present invention.
According to the embodiment of the invention, the farthest detection distance of the sensor to be detected and the projection position of the position point positioned at the farthest detection distance in the sensing data are determined according to the sensing data of the sensor to be detected; and determining whether the detection range of the sensor to be detected is abnormal or not according to the farthest detection distance of the sensor to be detected and the projection position of the position point positioned at the farthest detection distance, thereby realizing the abnormal detection of the detection range of the sensor to be detected.
In addition, the application of the projection position of the position point at the farthest detection distance in the sensing data avoids the misjudgment of the abnormal detection range of the sensor to be detected only according to the farthest detection distance of the sensor to be detected because the sensor to be detected is surrounded by the obstacle at a short distance.
Drawings
Fig. 1 is a flowchart of an anomaly detection method according to an embodiment of the present invention;
fig. 2 is a flowchart of an anomaly detection method according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of an abnormality detection apparatus according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of an anomaly detection method according to an embodiment of the present invention. The present embodiment is applicable to the case where abnormality detection of the maximum detection range is performed on the sensor under test based on the sensed data. Typically, the present embodiment is applicable to a case where detection of whether or not the maximum detection range of the laser radar sensor in the autonomous vehicle is narrowed is performed based on the point cloud data. The method may be performed by an anomaly detection apparatus, which may be implemented in software and/or hardware. Referring to fig. 1, the abnormality detection method provided in this embodiment includes:
s110, determining the farthest detection distance of the sensor to be detected and the projection position of a position point located at the farthest detection distance in the sensing data according to the sensing data of the sensor to be detected.
The sensor to be detected is any sensor capable of detecting three-dimensional space characteristic data of the space position point. Specifically, the sensor to be measured may be a laser radar sensor, a millimeter wave radar sensor, or other radar sensors. This implementation does not impose any limitations on this.
The three-dimensional spatial feature data is data describing a three-dimensional position space of the spatial position points, and may specifically include X-axis data, Y-axis data, and Z-axis data.
The sensed data is data including three-dimensional spatial features acquired by a sensor to be measured. Typically, the sensed data is point cloud data.
The point cloud data is a mass of point data obtained by scanning a sensor to be detected, wherein each position point included in the point cloud data has a three-dimensional coordinate (x, y, z). The position of the sensor to be detected is taken as an original point in a coordinate axis of the point cloud data, a positive X axis represents the front of the sensor to be detected, a negative X axis represents the rear of the sensor to be detected, a positive Y axis represents the left side of the sensor to be detected, a negative Y axis represents the right side of the sensor to be detected, a positive Z axis represents the upper side of the sensor to be detected, and a negative Z axis represents the lower side of the sensor to be detected.
Specifically, the determining the farthest detection distance of the sensor to be detected according to the sensing data of the sensor to be detected includes:
determining the distance between each position point in the sensing data and the sensor to be detected according to the three-dimensional space characteristic data of each position point in the sensing data of the sensor to be detected;
and taking the maximum value of the distances as the farthest detection distance.
Typically, the distance between each position point in the sensing data and the sensor to be measured is determined according to the data of the X-axis and the Y-axis in the sensing data of the sensor to be measured.
The calculation of the distance between each position point in the sensing data and the sensor to be measured may be:
Figure GDA0003227766110000061
where X is the data for the X-axis of the location point and Y is the location data for the Y-axis of the location point.
Specifically, the determining, according to sensing data of a sensor to be detected, a projection position of a position point located at a farthest detection distance in the sensing data includes:
and if the height of the position point at the farthest detection distance is determined to be smaller than a set height threshold value according to the three-dimensional space characteristic data of the position point in the sensing data, determining that the projection position of the position point is the ground, otherwise, determining that the projection position of the position point is on the obstacle.
The set height threshold refers to a maximum height value of the position point where the ground belongs to in the sensing data. The specific setting can be according to actual need.
Typically, the height of the position point located at the farthest detection distance may be determined according to the Z-axis value of the position point located at the farthest detection distance in the sensed data.
S120, determining whether the detection range of the sensor to be detected is abnormal or not according to the farthest detection distance of the sensor to be detected and the projection position of the position point located at the farthest detection distance.
Specifically, the determining whether the detection range of the sensor to be detected is abnormal according to the farthest detection distance of the sensor to be detected and the projection position of the position point located at the farthest detection distance includes:
if the farthest detection distance of the sensor to be detected is smaller than a set distance threshold value, and the projection position of the position point which is larger than the set number threshold value in the position points at the farthest detection distance is the ground, determining the sensing data as detection range reduction data;
and if the number of times of continuously monitoring the reduction data of the detection range is larger than a set number threshold, determining that the detection range of the sensor to be detected is reduced.
Wherein, the set distance threshold is the minimum value of the farthest detection distance under the normal condition of the detection range. The specific setting can be according to actual need. For example, if the automatic driving strategy is affected when the farthest detection distance is less than 10 meters, the set distance threshold may be set to 10 meters.
The set number threshold is the minimum value of the projection position of the position point at the farthest detection distance on the ground when the detection range of the sensor to be detected is reduced.
The projection positions of the position points which are greater than the set number threshold value in the position points at the farthest detection distance are set as the screening conditions of the ground, so that the misjudgment of the abnormality of the detection range of the sensor to be detected only according to the farthest detection distance of the sensor to be detected due to the fact that the sensor to be detected is surrounded by the obstacles at a close distance is effectively avoided.
For example, when an autonomous vehicle travels with a sensor to be measured to a location surrounded by a building for a full circle. If the farthest detection distance of the sensor to be detected is directly used, the sensor to be detected may be erroneously judged as a reduction in the detection range due to shielding of surrounding buildings. And the projection positions of the position points which are greater than the set number threshold value in the position points at the farthest detection distance are the screening conditions of the ground, so that the condition is effectively avoided.
Optionally, the determining whether the detection range of the sensor to be detected is abnormal according to the farthest detection distance of the sensor to be detected and the projection position of the position point located at the farthest detection distance includes:
if the farthest detection distance of the sensor to be detected is greater than a set maximum distance threshold value, and the projection position of the position point which is greater than a set number threshold value in the position points at the farthest detection distance is the ground, determining the sensing data as detection range expansion data;
and if the number of times of continuously monitoring the detection range expansion data is larger than a set number threshold, determining that the detection range of the sensor to be detected is expanded.
The maximum distance threshold is set to be the maximum value of the maximum detection distance under the normal condition of the detection range.
The detection range of the sensor to be detected can be reduced and enlarged through the steps.
According to the technical scheme of the embodiment of the invention, the farthest detection distance of the sensor to be detected and the projection position of the position point positioned at the farthest detection distance in the sensing data are determined according to the sensing data of the sensor to be detected; and determining whether the detection range of the sensor to be detected is abnormal or not according to the farthest detection distance of the sensor to be detected and the projection position of the position point positioned at the farthest detection distance, thereby realizing the abnormal detection of the detection range of the sensor to be detected.
In addition, the application of the projection position of the position point at the farthest detection distance in the sensing data avoids the misjudgment of the abnormal detection range of the sensor to be detected only according to the farthest detection distance of the sensor to be detected because the sensor to be detected is surrounded by the obstacle at a short distance.
Example two
Fig. 2 is a flowchart of an anomaly detection method according to a second embodiment of the present invention. The embodiment is an alternative provided by taking the sensor to be measured as a laser radar sensor applied to the automatic driving vehicle and sensing data as point cloud data on the basis of the embodiment. Referring to fig. 2, the abnormality detection method provided in this embodiment includes:
s210, judging whether the farthest detection distance of the laser radar sensor is smaller than a set distance threshold value according to X-axis data and Y-axis data in the acquired point cloud data.
And S220, if so, judging whether the projection position of the position point positioned at the farthest detection distance in the point cloud data is on the obstacle or on the ground according to the Z-axis data in the point cloud data.
And if the Z-axis value of the position point which is positioned at the farthest detection distance in the point cloud data is smaller than the set height threshold value, determining that the projection position of the position point is the ground.
And S230, if the projection position of the position point located at the farthest detection distance is on the ground, and the probability that the projection position of the position point located at the farthest detection distance is the position point of the ground is greater than a set probability threshold, determining that the detection distance of the laser radar sensor is shortened.
The set probability threshold is the minimum value of the ratio of the number of the position points at the farthest detection distance of the projection position to the total number of the position points at the farthest detection distance of the ground under the condition that the detection range of the laser radar sensor to be detected is reduced.
And S240, reporting to a safety redundancy system for alarming or braking.
According to the technical scheme of the embodiment of the invention, the warning or braking treatment is realized when the detection range of the laser radar sensor in the automatic driving vehicle is reduced to the set distance threshold value. The driving safety problem caused by the influence of the detection range reduction of the laser radar sensor on the automatic driving strategy is avoided.
It should be noted that, after the technical teaching of the present embodiment, a person skilled in the art may motivate a combination of any one of the implementation manners described in the above embodiments to implement the anomaly detection on the detection range of the sensor under test.
EXAMPLE III
Fig. 3 is a schematic structural diagram of an abnormality detection apparatus according to a third embodiment of the present invention. The abnormality detection apparatus provided in the present embodiment includes: a data determination module 10 and an anomaly detection module 20.
The data determining module 10 is configured to determine, according to sensing data of a sensor to be detected, a farthest detection distance of the sensor to be detected and a projection position of a position point located at the farthest detection distance in the sensing data;
and the anomaly detection module 20 is configured to determine whether the detection range of the sensor to be detected is abnormal according to the farthest detection distance of the sensor to be detected and the projection position of the position point located at the farthest detection distance.
According to the technical scheme of the embodiment of the invention, the farthest detection distance of the sensor to be detected and the projection position of the position point positioned at the farthest detection distance in the sensing data are determined according to the sensing data of the sensor to be detected; and determining whether the detection range of the sensor to be detected is abnormal or not according to the farthest detection distance of the sensor to be detected and the projection position of the position point positioned at the farthest detection distance, thereby realizing the abnormal detection of the detection range of the sensor to be detected.
In addition, the application of the projection position of the position point at the farthest detection distance in the sensing data avoids the misjudgment of the abnormal detection range of the sensor to be detected only according to the farthest detection distance of the sensor to be detected because the sensor to be detected is surrounded by the obstacle at a short distance.
Further, the data determination module includes: a distance determination unit and a farthest distance determination unit.
The distance determining unit is used for determining the distance between each position point in the sensing data and the sensor to be detected according to the three-dimensional space characteristic data of each position point in the sensing data of the sensor to be detected;
a farthest distance determination unit configured to take a maximum value of the distances as a farthest detection distance.
Further, the data determination module includes: a projection position determination unit.
The projection position determining unit is used for determining that the projection position of the position point is the ground if the height of the position point located at the farthest detection distance is determined to be smaller than a set height threshold value according to the three-dimensional space characteristic data of the position point in the sensing data.
Further, the anomaly detection module includes: a reduced data determination unit and a range reduction determination unit.
The reduced data determining unit is used for determining the sensing data as reduced detection range data if the farthest detection distance of the sensor to be detected is smaller than a set distance threshold value and the projection position of a position point which is larger than a set number threshold value in position points at the farthest detection distance is the ground;
and the range reduction determining unit is used for determining that the detection range of the sensor to be detected is reduced if the number of times of continuously monitoring the detection range reduction data is greater than a set number threshold.
The anomaly detection device provided by the embodiment of the invention can execute the anomaly detection method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
Example four
Fig. 4 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention. FIG. 4 illustrates a block diagram of an exemplary electronic device 12 suitable for use in implementing embodiments of the present invention. The electronic device 12 shown in fig. 4 is only an example and should not bring any limitation to the function and the scope of use of the embodiment of the present invention.
As shown in FIG. 4, electronic device 12 is embodied in the form of a general purpose computing device. The components of electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, micro-channel architecture (MAC) bus, enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Electronic device 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by electronic device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. The electronic device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 4, and commonly referred to as a "hard drive"). Although not shown in FIG. 4, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
Electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), with one or more devices that enable a user to interact with electronic device 12, and/or with any devices (e.g., network card, modem, etc.) that enable electronic device 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. Also, the electronic device 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet) via the network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 via the bus 18. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 16 executes various functional applications and data processing by executing programs stored in the system memory 28, for example, implementing the abnormality detection method provided by the embodiment of the present invention.
EXAMPLE five
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements an abnormality detection method according to any embodiment of the present invention, where the method includes:
determining the farthest detection distance of the sensor to be detected and the projection position of a position point positioned at the farthest detection distance in the sensing data according to the sensing data of the sensor to be detected;
and determining whether the detection range of the sensor to be detected is abnormal or not according to the farthest detection distance of the sensor to be detected and the projection position of the position point positioned at the farthest detection distance.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, 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. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, 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 computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims (10)

1. An abnormality detection method characterized by comprising:
determining the farthest detection distance of the sensor to be detected and the projection position of a position point positioned at the farthest detection distance in the sensing data according to the sensing data of the sensor to be detected;
carrying out reduction detection or expansion detection on the detection range of the sensor to be detected according to the farthest detection distance of the sensor to be detected and the projection position of the position point positioned at the farthest detection distance;
and if the farthest detection distance of the sensor to be detected is greater than a set maximum distance threshold value, and the projection position of the position point which is greater than a set number threshold value in the position points at the farthest detection distance is the ground, determining the sensing data as detection range expansion data.
2. The method of claim 1, wherein determining the farthest detection distance of the sensor under test from the sensing data of the sensor under test comprises:
determining the distance between each position point in the sensing data and the sensor to be detected according to the three-dimensional space characteristic data of each position point in the sensing data of the sensor to be detected;
and taking the maximum value of the distances as the farthest detection distance.
3. The method of claim 1, wherein determining the projected location of the location point located at the farthest detection distance in the sensed data from the sensed data of the sensor under test comprises:
and if the height of the position point at the farthest detection distance is determined to be smaller than a set height threshold value according to the three-dimensional space characteristic data of the position point in the sensing data, determining that the projection position of the position point is the ground.
4. The method of claim 1, wherein the detecting the reduction of the detection range of the sensor under test according to the farthest detection distance of the sensor under test and the projected position of the position point at the farthest detection distance comprises:
if the farthest detection distance of the sensor to be detected is smaller than a set distance threshold value, and the projection position of the position point which is larger than the set number threshold value in the position points at the farthest detection distance is the ground, determining the sensing data as detection range reduction data;
and if the number of times of continuously monitoring the reduction data of the detection range is larger than a set number threshold, determining that the detection range of the sensor to be detected is reduced.
5. An abnormality detection device characterized by comprising:
the data determination module is used for determining the farthest detection distance of the sensor to be detected and the projection position of a position point positioned at the farthest detection distance in the sensing data according to the sensing data of the sensor to be detected;
the abnormality detection module is used for carrying out reduction detection or expansion detection on the detection range of the sensor to be detected according to the farthest detection distance of the sensor to be detected and the projection position of the position point positioned at the farthest detection distance; and if the farthest detection distance of the sensor to be detected is greater than a set maximum distance threshold value, and the projection position of the position point which is greater than a set number threshold value in the position points at the farthest detection distance is the ground, determining the sensing data as detection range expansion data.
6. The apparatus of claim 5, wherein the data determination module comprises:
the distance determining unit is used for determining the distance between each position point in the sensing data and the sensor to be detected according to the three-dimensional space characteristic data of each position point in the sensing data of the sensor to be detected;
a farthest distance determination unit configured to take a maximum value of the distances as a farthest detection distance.
7. The apparatus of claim 5, wherein the data determination module comprises:
and the projection position determining unit is used for determining that the projection position of the position point is the ground if the height of the position point at the farthest detection distance is determined to be smaller than a set height threshold value according to the three-dimensional space characteristic data of the position point in the sensing data.
8. The apparatus of claim 5, wherein the anomaly detection module comprises:
the reduced data determining unit is used for determining the sensing data as reduced detection range data if the farthest detection distance of the sensor to be detected is smaller than a set distance threshold value and the projection position of the position point which is larger than the set number threshold value in the position points at the farthest detection distance is the ground;
and the range reduction determining unit is used for determining that the detection range of the sensor to be detected is reduced if the number of times of continuously monitoring the detection range reduction data is greater than a set number threshold.
9. An electronic device, characterized in that the electronic device comprises:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the anomaly detection method of any one of claims 1-4.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the anomaly detection method according to any one of claims 1 to 4.
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