A method for detecting degradation of a ridiculometer sensor, and a method for operating a vehicle and / or robot.

Abstract

The invention relates to a method for detecting degradation of a lidar sensor, comprising emitting lidar pulses by a lidar sensor, detecting reflections of the emitted lidar pulses by the lidar sensor, detecting an object (O) reflecting the lidar pulses in an environment surrounding the lidar sensor, tracking the detected object (O) over a number of time cycles, determining the lidar pulses that would be reflected by the object when tracking the object (O) taking into account a distance (d) of the tracked object (O) to the lidar sensor and a geometry of the tracked object (O), determining a failure rate (a) indicative of how often an expected reflection is not detected within a predefined period of time, and inferring degradation of the lidar sensor based on the failure rate (a) and the distance (d) to the tracked object (O). The invention further relates to a method for operating a vehicle and / or a robot.

Description

Technical Field

[0001] The present invention relates to a method for detecting deterioration of a lidar sensor.

[0002] The present invention further relates to a method for operating a vehicle and / or a robot.

Background Art

[0003] From German Patent Application Publication No. 102018008903, a method for determining the field of view of a beam-based sensor of a vehicle for detecting the surrounding environment is known. By means of the beam-based sensor, a sensor beam of a known intensity is emitted, the reflection of the sensor beam is detected by the sensor, and the reflection intensity is evaluated. The measured distance and the reflection intensity are correlated with each other, and it is determined whether the field of view of the sensor is reduced compared to the maximum field of view of the sensor.

Summary of the Invention

Problems to be Solved by the Invention

[0004] An object of the present invention is to provide a novel method for detecting deterioration of a lidar sensor and a novel method for operating a vehicle and / or a robot.

Means for Solving the Problems

[0005] According to the present invention, the above object is achieved by a method for detecting deterioration of a lidar sensor having the features described in claim 1 and a method for operating a vehicle and / or a robot having the features described in claim 6.

[0006] Advantageous embodiments of the present invention are the subject matter of the dependent claims.

[0007] According to the present invention, in a method for detecting degradation of a lidar sensor, the lidar sensor emits a lidar pulse, and the reflection of the emitted lidar pulse is detected by the lidar sensor. Furthermore, an object that reflects the lidar pulse is detected in the environment surrounding the lidar sensor, and the detected object is tracked over multiple time cycles. Considering the distance of the tracked object to the lidar sensor and the geometry of the tracked object, the lidar pulse that will be reflected by the object during tracking is determined. Furthermore, a failure rate is determined, which indicates how often the expected reflection is not detected within a given period. Based on the failure rate and the distance to the tracked object, the degradation of the lidar sensor is estimated.

[0008] This method not only determines the current degradation of a lidar sensor, which is affected, for example, by the influence of the surrounding environment or dirt, but also enables a reliable determination of the aging degradation and loss of individual transmitter-receiver pairs of the lidar sensor. This information can be used to adapt the current driving style of a vehicle and / or robot to the degradation of the lidar sensor, and to identify the aging degradation state of the lidar sensor. Therefore, this information enables particularly reliable and safe operation of automated, especially highly automated, or autonomous vehicles and / or robots.

[0009] In a possible embodiment of this method, a decrease in the range of the lidar sensor is defined as degradation. Therefore, the current driving style of the vehicle and / or robot can be adapted to the current range of the lidar sensor. For example, as degradation of at least one lidar sensor progresses, the driving speed of the vehicle and / or robot can be reduced.

[0010] In another possible embodiment of this method, the failure rate is determined for each receiver pixel of the lidar sensor. This ensures that if some of the lidar sensor degrades, the information detected by receiver pixels outside the degraded area can still be reliably used for the vehicle's automated operation, thereby minimizing limitations on automated operation.

[0011] In another possible embodiment of this method, to determine the defects and / or aging of each receiver pixel, a comparison is made between the determined failure rate of each receiver pixel and the determined failure rate of adjacent receiver pixels, depending on the distance to the tracked object. This can further enhance the reliability of this method.

[0012] In another possible embodiment of this method, the range of the lidar sensor is determined by the reflection intensity of the lidar pulse reflected by an object and the distance of the lidar sensor to the object. Such range determination can be performed particularly simply, reliably, and accurately.

[0013] In a method for operating a vehicle and / or robot according to the present invention, the surrounding environment of the vehicle and / or robot is detected by at least one lidar sensor, and automatic, in particular highly automatic, or autonomous driving operation of the vehicle and / or robot is performed depending on the data detected by the lidar sensor, taking into account the degradation of the at least one lidar sensor detected by the aforementioned method.

[0014] This method ensures reliable detection of lidar sensor degradation, thereby guaranteeing the operation of autonomous vehicles to the same degree, and thus improving traffic safety.

[0015] In a conceivable embodiment of this method, during autonomous driving, the vehicle and / or robot's driving speed is reduced as the degradation of at least one lidar sensor progresses, thereby enabling safe vehicle operation and a high level of traffic safety at all times, depending on the degradation of the lidar sensor.

[0016] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. [Brief explanation of the drawing]

[0017] [Figure 1] This diagram schematically shows the receiver of a lidar sensor when an object is detected at a first distance. [Figure 2] FIG. 1 schematically shows a receiver according to FIG. 1 when an object is detected at a second distance shorter than the first distance. [Figure 3] FIG. 4 schematically shows a receiver of a lidar sensor when detecting an object. [Figure 4] FIG. 7 schematically shows a failure rate of a receiver of a lidar sensor according to the distance to a detected object.

DETAILED DESCRIPTION OF THE INVENTION

[0018] In all the figures, corresponding parts are denoted by the same reference numerals.

[0019] FIG. 1 schematically shows a receiver 1 of a lidar sensor when an object O is detected at a first distance d. FIG. 2 shows the receiver 1 according to FIG. 1 when the object O is detected at a second distance d shorter than the first distance d. The distance d is shown in detail in FIG. 4.

[0020] The lidar sensor scans its surrounding environment with light in the infrared region and detects, for each measurement point or receiver pixel 1.1 to 1.n, an interval or distance d and information regarding the backscattered light. This information is, for example, the intensity of the backscattered light. Based on the measurement principle, since the receiver 1 of the lidar sensor measures in polar coordinates, the number of measurement points or receiver pixels 1.1 to 1.n per unit area decreases as the distance d increases.

[0021] As a result, as schematically shown in FIG. 1, on an object O at a large distance d from the receiver 1, for example, 150 m, the number of receiver pixels 1.1 to 1.n that receive a signal is smaller than when detecting an object O according to FIG. 2 where the distance d is much smaller. When the object O is measured several times and tracked over time, it is possible to collate the frequency with which individual receiver pixels 1.1 to 1.n fail to receive a signal, even though a signal is expected at the receiver pixels 1.1 to 1.n based on the existing object dimensions.

[0022] Figure 3 shows the receiver 1 of the lidar sensor when the object O is detected. Here, the object O is designed to be detected by the reception pixels 1.3 to 1.5, 1.12 to 1.14, 1.21 to 1.23, and 1.30 to 1.32. Figure 4 shows the failure rate a of various reception pixels 1.1 to 1.n of the lidar sensor depending on the distance d to the detected object O.

[0023] If the object O is first detected at the first time point t_0 and then continuously tracked through another time point t_k and further to another time point t_m over time, the failure rate a for each of the receiver pixels 1.1 to 1.n of the lidar sensor can be determined based on known geometry. Here, the failure rate a can be combined with the distance d of the object O between the aforementioned first time point t_0 and another time point t_m. Therefore, the failure rate a depending on the distance d can be determined for each of the reception pixels 1.1 to 1.n.

[0024] By comparing the failure rate a determined depending on the distances between different receiver pixels 1.1 to 1.n, it becomes possible to infer possible defects or deteriorations of the receiver pixels 1.1 to 1.n. In that case, possible temporary disturbances such as rain or dirt on the front glass of the lidar sensor can be identified by various temporal accumulations.

[0025] If the failure rate a is determined in the laboratory depending on the distance d at the start of the life cycle of the lidar sensor, these values can be used as a basis for determining temporary or continuous changes.

[0026] Figure 3 shows an example of the difference that occurs between the receiver pixel 1.13 and the defective receiver pixel 1.22 when the object O is detected. The 100% failure rate a shown in Figure 4 indicates no measurement, that is, the receiver 1 of the lidar sensor did not recognize any object O.

[0027] Here, the failure rate a, determined by distance d, allows for the following inference. The relationship between the maximum reach of the lidar sensor and the failure rate a is as follows: When β=f(a), d max =β·d(t k ) (1) Here, the coefficient β can be determined based on laboratory measurements or measurements from previous sensors and depends on the failure rate a.

[0028] Therefore, for example, it would be as follows: a(d(t k If ))=25% and β=f(a)=f(25%)=1.25, d max = 1.25·d(t k ) (2)

[0029] Here, the difference in failure rate curves between two different receiver pixels 1.1 to 1.n can be caused persistently by defects or degradation of electronic and / or optical components, and / or temporarily by external disturbances such as dirt on the lidar sensor's windshield, or, for example, rain or fog. This is shown in Figure 4 with respect to the failure rate a(1.22) of the defective receiver pixel 1.22 and the failure rate a(1.13) of the adjacent receiver pixel 1.13. [Prior art documents] [Patent Documents]

[0030] [Patent Document 1] German Patent Application Publication No. 102018008903 Specification

Claims

1. A method for detecting degradation of a lidar sensor, - The ridica sensor emits a ridica pulse, - The reflection of the emitted rida pulse is detected by the rida sensor, - An object (O) that reflects the ridica pulse is detected in the surrounding environment of the ridica sensor, - The detected object (O) is tracked over multiple time cycles, - Considering the distance (d) of the tracked object (O) to the ridiculometer and the geometry of the tracked object (O), the ridiculometer pulses that will be reflected by the object (O) during tracking are determined. - A failure rate (a) is determined, which indicates the frequency at which the expected reflection is not detected within a predetermined period. - Based on the failure rate (a) and the distance (d) to the tracked object (O), the degradation of the ridiculum sensor is estimated. method.

2. A decrease in the maximum reach of the ridda sensor (d max), obtained by multiplying a coefficient (β(a)) that can be determined based on laboratory measurements or measurements with a previous line sensor and depends on the failure rate (a), by the distance (d) of the tracked object (O) to the ridda sensor, is determined as degradation. The method according to claim 1, characterized in that

3. The failure rate (a) is determined for each receiver pixel (1.1 to 1.n) of the ridda sensor. The method according to claim 1 or 2, characterized in that

4. To determine defects and / or aging degradation of each of the receiver pixels (1.1 to 1.n), a comparison is made between the determined failure rate (a) of each receiver pixel (1.1 to 1.n) and the determined failure rate (a) of adjacent receiver pixels (1.1 to 1.n), depending on the distance (d) to the tracked object (O). The method according to claim 3, characterized in that

5. A method for operating a vehicle and / or robot, - The surrounding environment of the vehicle and / or robot is detected by at least one lidar sensor, - Depending on the data detected by the lidar sensor, the automatic operation or autonomous driving operation of the vehicle and / or robot is performed taking into account the degradation of the at least one lidar sensor detected by the method of claim 1 or 2. method.

6. In autonomous driving operation, the vehicle and / or robot's driving speed is reduced as the degradation of at least one lidar sensor progresses. The method according to claim 5, characterized in that

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