METHOD AND DEVICE FOR DETECTING AN OBSTACLE FOR LIDAR AND STORAGE MEDIUM

Abstract

A method for detecting an obstacle, comprising: a detection pulse signal is emitted to scan the obstacle within a measurement time window; the measurement time window is configured to determine a flight time between the emission of a scanning pulse signal to detect a target object and the reception of an echo from the target object; a scattered light echo corresponding to the detection pulse signal is received; the presence of the obstacle is determined based on a feature parameter of the scattered light echo.

Description

CROSS-REFERENCE TO RELATED REGISTRATION(S)

[0001] The present application claims priority over Chinese patent application No. 202211566326.1, filed on December 7, 2022, the contents of which are hereby incorporated in their entirety by reference. TECHNICAL AREA

[0002] The present disclosure relates to the field of LiDARs and in particular LiDARs, methods and devices for detecting an obstacle thereto, as well as storage media. BACKGROUND

[0003] The LiDAR is an important sensor for autonomous driving. A LiDAR can include a laser transmitter, a laser receiver, and a light cover (which can also be called a "window"). The light cover is a crucial component of the laser transmission and reception paths. It protects the LiDAR's internal optical and electronic components and shields it from external ambient light. The LiDAR is a non-contact measuring device. The cleanliness of the light cover and any obstructions blocking the light exit path can directly affect the distance measurement and accuracy. In a coaxial optical system, the light transmitter generates scattered light within the LiDAR when producing a beam. This scattered light is reflected within the LiDAR and received by the light receiver, creating a scattered light echo.The scattered light echo can be localized within a fixed time window.

[0004] Referring to Fig. 1. Contamination is located on the light cover of a LiDAR with a coaxial optical system. When the LiDAR's light source emits a scanning pulse signal, the contamination reflects the signal, generating stray light. This stray light can be reflected within the LiDAR and received by the light receiver, creating a stray light echo.

[0005] Typically, the potential impact of pollution on the light coverage of the LiDAR point cloud essentially includes: 1) The power of the scanning light beam striking a target object may be attenuated. The measurement capability and the reflectance may be reduced. 2) After the light beam is reflected by the target object, the power of the light beam falling on the LiDAR's light receiver may be attenuated. This can reduce the measurement capability and reflectance. 3) The direction of the scanning light beam emitted by the LiDAR light cover changes, so the position information of parts of the point cloud may be inaccurate. 4) The echo reflected by the pollution can cause an increase in the noise signal in the point cloud.

[0006] Referring to Fig. 2. The scattered light echo is formed almost simultaneously after the emission of the sampling pulse signal by the light source. If the emission time of the sampling pulse signal is determined, the waveform of the scattered light echo can be localized within a relatively fixed time window. The temporal relationship between the sampling pulse signal and the waveform of the scattered light echo is shown by the curves in Fig.Figure 2 shows the time sequence of the sampling pulse signal. Curve 1 represents the waveform of the stray light techno before the light cover becomes dirty. Curve 3 represents the waveform of the stray light techno after the light cover becomes dirty.

[0007] The sampling pulse signal can be emitted within an emission time window. The scattered light echo is collected in front of an object echo. If dirt or other obstructions are present on the light cover, the peak value (maximum value), pulse width, and integral value of the scattered light echo can increase to a certain extent. The dirt or other obstruction can thus be detected.

[0008] Referring to Fig.Figure 3 represents the horizontal axis as the time-of-flight (TOF) and the vertical axis as the voltage waveform. The light source can emit a sampling pulse signal within an emission time window. The light receiver can receive a scattered light echo in front of the object echo. The waveform of the scattered light echo when there is no obstacle on the light cover and the waveform of the scattered light echo when there is an obstacle on the light cover are shown in Figure 3. Fig. 3 shown. Referring to Fig. 2 and Fig. 3. The obstacle causes an increase in the peak value, pulse width, and integral value of the scattered light techo, particularly the peak value and the integral value. The obstacle can be detected. For example, the obstacle can be identified by comparing the intensity of the scattered light techo within the time window t1-t2 with the threshold thres2.

[0009] In some embodiments, the LiDAR can use single-photon detectors. Because the single-photon detectors can receive the scattered light in the LiDAR first, many pixels of the single-photon detectors may no longer be able to scan the object echo. Detection capability can only be restored after a certain period. Measures to reduce scattered light are important for the detection capability of the single-photon detector. For example, the bias voltage of the single-photon detector can be controlled so that no bias voltage or only a very low voltage is applied to the single-photon detectors when the scanning pulse signal is emitted. However, the scattered light echo can fundamentally be a short-range echo, which means that the photon scanning efficiency of the detector may still be very low when the scattered light echo arrives.The received scattered light echo may be very weak or even disappear completely, leading to a poor detection result of the obstacle. SUMMARY

[0010] The present disclosure provides LiDARs, methods and devices for detecting an obstacle (obstruction of view, blockage, or barrier), as well as storage media for this purpose. The accuracy of obstacle detection can be improved.

[0011] In a first aspect, the present disclosure provides a method for detecting an obstacle for a LiDAR, wherein the method comprises: transmitting a detection pulse signal within a measurement time window, the measurement time window being configured to determine a flight time between the transmission of a scanning pulse signal for scanning a target object and the reception of an echo from the target object; receiving a scattered light techos corresponding to the detection pulse signal; and determining whether an obstacle is present, based on a feature parameter of the scattered light techos.

[0012] Optionally, determining whether an obstacle is present, based on a feature parameter of the scattered light signal, includes determining the presence of the obstacle when an obstacle detection threshold is reached by the feature parameter of the scattered light signal. The feature parameter of the scattered light signal includes at least one of the pulse width, peak value, and integral value of the scattered light signal.

[0013] Optionally, the obstacle detection threshold is determined by counting the feature parameters of scattered light techos from a multitude of LiDARs with obstacles and the feature parameters of scattered light techos from a multitude of LiDARs without obstacles.

[0014] Optionally, the obstacle detection threshold is dynamically adjusted based on changes in the environment in which the LiDAR is located.

[0015] Optionally, transmitting a detection pulse signal within a measurement time window includes: transmitting the detection pulse signal within a first time window; or transmitting the detection pulse signal within a second time window. The first time window is located at an end point within the measurement time window, the second time window is located within the measurement time window. The second time window is modified based on the reception time of the echo from the target object.

[0016] Optionally, the measurement time window comprises a first measurement time window and a second measurement time window, and the transmission of a detection pulse signal within a measurement time window comprises: transmission of the detection pulse signal within the first measurement time window, wherein the first measurement time window is configured to determine a flight time between the transmission of a sampling pulse signal to scan a short-range target and the reception of an echo from the short-range target; and / or transmission of the detection pulse signal within the second measurement time window, wherein the second measurement time window is configured to determine a flight time between the transmission of a sampling pulse signal to scan a long-range target and the reception of an echo from the long-range target.

[0017] Optionally, the duration of a time window for scanning the obstacle can be shorter than the duration of the measurement time window.

[0018] Optionally, the light intensity of the detection pulse signal can be lower than the light intensity of the sampling pulse signal.

[0019] Optionally, the light intensity of the detection pulse signal is selected from a range of light intensities, with the maximum value of the range of light intensities being determined by counting the light intensities of detection pulse signals based on the determination that there is no obstacle, a multitude of LiDARs without obstacles, and the minimum value of the range of light intensities being determined by counting the light intensities of detection pulse signals that produce identifiable stray light techos, a multitude of LiDARs with obstacles.

[0020] Optionally, the procedure for detecting an obstacle for a LiDAR further includes: determining an area in which the obstacle is located based on a deviation of the point cloud features between first point cloud data and second point cloud data, where the first point cloud data are the point cloud data collected before the obstacle was detected, the second point cloud data are point cloud data collected after the obstacle was detected, and the deviation of the point cloud features includes a distance deviation and / or a reflectance deviation.

[0021] Optionally, determining an area where the obstacle is located based on a deviation in point cloud features between first point cloud data and second point cloud data includes: determining abnormal point cloud data in the second point cloud data based on the deviation in point cloud features; and determining the area where the obstacle is located based on a sampling field of view of a sampling pulse signal corresponding to the abnormal point cloud data.

[0022] Optionally, the procedure for detecting an obstacle further includes: If an obstacle is detected based on several successive frames of point clouds in one and the same area, it is determined that the obstacle is present in that area.

[0023] Optionally, the procedure for detecting an obstacle further includes: determining an area in which the obstacle is located based on a position where a light transmitter channel emitting the detection pulse signal is located in a vertical direction, and a horizontal field of view corresponding to the light transmitter channel.

[0024] Optionally, the area in which the obstacle is located includes a vertical position and a horizontal position, and determining an area in which the obstacle is located, based on a position where a light source channel emitting the detection pulse signal is located in the vertical direction and a horizontal field of view corresponding to the light source channel, includes: determining the vertical position based on the position of a light source group in which the light source channel is located, in the vertical direction; and determining the horizontal position based on the horizontal field of view.

[0025] Optionally, the procedure for detecting an obstacle further includes: counting a multitude of areas in which a particular obstacle is located; and if the multitude of areas are spatially contiguous, determining that the obstacle is present in the multitude of areas.

[0026] Optionally, the stray light techos are echoes corresponding to the detection pulse signals emitted by a multitude of light transmitter channels in several light transmitter groups, and the method further comprises: counting the number of first light transmitter channels corresponding to the stray light techos reaching an obstacle detection threshold in each light transmitter group; and when the number of first light transmitter channels in the same light transmitter group reaches a first threshold, determining that the obstacle is present.

[0027] Optionally, determining whether an obstacle is present based on a feature parameter of the scattered light techos includes determining the presence of a first obstacle upon reaching a first obstacle detection threshold through the feature parameter of the scattered light techos, where the type of the first obstacle is a permeable obstacle; and determining the presence of a second obstacle upon reaching a second obstacle detection threshold through the feature parameter of the scattered light techos, where the type of the second obstacle is an impermeable obstacle and the second obstacle detection threshold is greater than the first obstacle detection threshold.

[0028] Optionally, the stray light techos are echoes corresponding to the detection pulse signals emitted by a multitude of light transmitter channels in multiple light transmitter groups, and the method further comprises: when determining the presence of an obstacle, counting the number of first light transmitter channels corresponding to the stray light techos reaching an obstacle detection threshold in each light transmitter group; and determining a type of obstacle based on the number of first light transmitter channels.

[0029] Optionally, the obstacle detection procedure further includes: issuing alarm messages upon determining the presence of an obstacle; the alarm messages being used to indicate one or more of the following: the presence of the obstacle, an area in which the obstacle is located, a type of obstacle, and control information, the control information being used to control the LiDAR or a device mounted on the LiDAR.

[0030] In a second aspect, the present disclosure provides a device for detecting an obstacle for a LiDAR, comprising: a control module configured to control the emission of a detection pulse signal for scanning the obstacle within a measurement time window and to control the reception of a scattered light echo corresponding to the detection pulse signal, wherein the measurement time window is configured to determine a flight time between the emission of a scanning pulse signal for scanning a target object and the reception of an echo from the target object; and a detection module configured to determine, based on a feature parameter of the scattered light echo, whether an obstacle is present.

[0031] In a third aspect, the present disclosure provides a computer-readable storage medium with a computer program stored thereon, wherein the computer program, when executed by a computer, performs the steps of the method for detecting an obstacle for a LiDAR.

[0032] In a fourth aspect, the present disclosure provides a LiDAR comprising: a light emitter configured to emit a scanning pulse signal for scanning a target object and a detection pulse signal for scanning an obstacle; a light receiver configured to receive an echo generated by the scanning pulse signal via the target object and a scattered light echo corresponding to the detection pulse signal; and a controller with a computer program stored thereon, wherein, when the computer program is executed, the controller performs the steps of the obstacle detection method for a LiDAR.

[0033] In a fifth aspect, the present disclosure further provides an end device comprising a memory and a processor, wherein a computer program is stored in the memory which is executable on the processor, and the processor, when executing the computer program, performs the steps of the previously described method for detecting an obstacle for a LiDAR.

[0034] Optionally, the terminal device includes a LiDAR, a vehicle, a drone, or a robot.

[0035] In the present disclosure, a light emitter of a LiDAR can transmit a detection pulse signal within a measurement time window to scan for an obstacle. A light receiver of the LiDAR can receive a scattered light echo corresponding to the detection pulse signal. Whether an obstacle is present can be determined based on a feature parameter of the scattered light echo. The detection pulse signal can be a pulse signal used to detect the obstacle. The detection pulse signal and the scanning pulse signal can be two independent pulse signals. Obstacle detection can be achieved without interfering with the detection of a target object. This prevents the scattered light echo generated by the detection pulse signal from being affected by the echo from the target object or by means of reducing scattered light. The accuracy of obstacle detection can be improved or ensured.Furthermore, the detection pulse signal is not used for distance measurement, and the echo from the target object does not need to be received as long as the stray light echo waveform is measurable. The measurement window for the stray light echo generated by the detection pulse signal can be short, which is feasible when the available time resources in the LiDAR are limited. Both target object detection and the obstacle detection function of the LiDAR can be achieved. Additionally, the light intensity of the detection pulse signal can be lower than the light intensity of the scanning pulse signal. The light intensity of the detection pulse signal in this disclosure can be configured such that the light receiver can receive and detect the stray light echo. The light intensity of the detection pulse signal can be set lower. The feature parameter of the stray light echo can change significantly if an obstacle is present.This makes it easier to detect the obstacle and reduces the impact on the target detection performance of the LiDAR. BRIEF DESCRIPTION OF THE DRAWINGS Fig. Figure 1 shows a schematic representation of contamination on a light cover that blocks the emission light path in the prior art. Fig. Figure 2 shows a schematic representation of a waveform of a scattered light techno in the prior art. Fig. Figure 3 shows a schematic representation of another waveform of a scattered light techno in the prior art. Fig. Figure 4 shows a flowchart of an example method for detecting an obstacle according to some embodiments of the present disclosure. Fig. Figure 5 shows a schematic representation of various exemplary echo waveforms according to some embodiments of the present disclosure. Fig.Figure 6 shows an exemplary schematic representation of a time window for sending a detection pulse signal according to some embodiments of the present disclosure. Fig. Figure 7 shows an exemplary schematic representation of another time window for sending a detection pulse signal according to some embodiments of the present disclosure. Fig. Figure 8 shows an exemplary schematic representation of a further time window for sending a detection pulse signal according to some embodiments of the present disclosure. Fig. Figure 9 shows a schematic representation of exemplary feature parameters of a scattered light techos according to some embodiments of the present disclosure. Fig. Figure 10 shows a schematic representation of an exemplary area division according to some embodiments of the present disclosure. Fig.Figure 11 shows a schematic representation of the energy of a sampling pulse signal from a laser according to some embodiments of the present disclosure. Fig. Figure 12 shows an exemplary schematic representation of pulse signals with different types of obstacles according to some embodiments of the present disclosure. Fig. Figure 13 shows a further exemplary schematic representation of pulse signals with different types of obstacles according to some embodiments of the present disclosure. Fig. Figure 14 shows a schematic structural representation of an example device for detecting an obstacle according to some embodiments of the present disclosure. Fig. Figure 15 shows an exemplary schematic structural representation of a LiDAR according to some embodiments of the present disclosure. DETAILED DESCRIPTION

[0036] A LiDAR can employ means of reducing stray light to ensure the detection capability of the single-photon detector and improve measurement performance. For example, the bias voltage of the single-photon detector can be controlled so that no bias voltage, or only a very low voltage, is applied to the single-photon detector when the sampling pulse signal is emitted. Since the stray light echo is typically a short-range echo, the photon sampling efficiency of the detector may still be very low when the stray light echo returns. The detected stray light echo is very weak, or the stray light echo may even disappear, as shown in curve 4 in [reference missing]. Fig.3. The intensity of the scattered light signal may not exceed the threshold thres2 at this point, resulting in poor detection of the obstacle and easily causing false detections. Furthermore, to ensure measurement capability, the LiDAR's sampling pulse signal may be strong and insensitive to changes (e.g., increases) in the scattered light feature parameters caused by the obstacle. The primary function of the sampling pulse signal is to scan the target object. The generation of a scattered light signal with a specific intensity for obstacle detection is not considered when setting the intensity of the sampling pulse signal.

[0037] In some embodiments, the detection pulse signal can be a pulse signal used for obstacle detection. The detection pulse signal and the scanning pulse signal are two independent pulse signals. Obstacle detection can be achieved without affecting target detection. The stray light echo can be unaffected by the target echo or by stray light reduction measures. Furthermore, the detection pulse signal cannot be used for distance measurement. The target echo does not need to be received, provided the stray light echo waveform is measurable. The stray light echo measurement window can be short. This is feasible when time resources are limited in the LiDAR. Both target detection and obstacle detection functions of the LiDAR can be achieved. Additionally, the detection pulse signal and the scanning pulse signal are independent of each other.The means for suppressing stray light can no longer be used when the detection pulse signal is emitted. This ensures the measurability of the stray light signal. Obstacle detection based on the stray light signal's feature parameter can be achieved. The accuracy of obstacle detection can be improved.

[0038] To clarify and improve the understanding of the aforementioned objectives, features and advantages of the application, some embodiments are described in detail below with reference to the drawings.

[0039] Fig. Figure 4 shows a flowchart of an example method for detecting an obstacle according to some embodiments of the present disclosure. Referring to Fig. 4, The example procedure can include the following steps.

[0040] In step 401, a detection pulse signal is sent within a measurement time window to detect an obstacle. The measurement time window is configured to determine the flight time between the transmission of a sampling pulse signal to scan a target object and the reception of an echo from the target object.

[0041] In step 402, a scattered light echo corresponding to the detection pulse signal is received.

[0042] In step 403, it is determined whether the obstacle is present based on a feature parameter of the scattered light techos.

[0043] In some embodiments, the obstacle can be, for example, dirt on the surface of the light cover or another short-range object besides the target object that blocks the emission light path and generates a scattered light echo. For instance, the obstacle could be a moving insect. Furthermore, the obstacle could be a weather or environmental phenomenon such as rain, snow, fog, frost, ice, haze, sandstorm, or similar. All of these obstacles can generate a scattered light echo.

[0044] In some embodiments, in step 401, the light emitter of a LiDAR can transmit a detection pulse signal within a measurement time window. The detection pulse signal is a pulse signal used to scan the obstacle. The scanning pulse signal is a pulse signal used to scan a target object. The detection pulse signal and the scanning pulse signal are two independent pulse signals. The measurement time window is configured to determine a flight time between the transmission of the scanning pulse signal and the reception of the echo from the target object.

[0045] If an obstacle is present, it can generate a scattered light echo for the detection pulse signal. For example, the obstacle can reflect or refract the detection pulse signal, creating a scattered light echo. In some embodiments, the LiDAR's light receiver can receive the scattered light echo in step 402.

[0046] In some embodiments, the obstruction can be contamination on the light cover. The scattered light echo can be generated almost simultaneously with the emission of the detection pulse signal by the light source. The time window in which the scattered light echo is localized can be determined based on the emission time of the detection pulse signal.

[0047] In some embodiments, the process for determining the time of flight can refer to the process in which the light source transmits the detection pulse signal, the light receiver receives the echo from the target object, and the LiDAR processes the echo. Accordingly, the measurement time window can comprise a time window 1 and a time window 2. Time window 1 is used for transmitting the scanning pulse signal and receiving the echo from the target object. Time window 2 is used for signal transmission and processing after receiving the echo. The duration of time window 1 is the time interval between the transmission of the detection pulse signal by the light source and the reception of the echo from the target object, corresponding to the maximum measurement capability of the LiDAR.

[0048] In some embodiments, after the echo from the target object has been received, the LiDAR may no longer be able to transmit a sampling pulse signal due to the long processing time of the echo within the time domain (e.g., within time window 2). The time domain can encompass the period between the reception of the echo from the target object by the light receiver and the end of the measurement time window. The detection pulse signal can be transmitted within this time domain. Thus, the detection pulse signal can be transmitted within time window 2. In some embodiments, the detection pulse signal can be transmitted within a first time window in step 401. The first time window can be located at the end of the measurement time window.

[0049] Fig. Figure 5 shows a schematic representation of various exemplary echo waveforms according to some embodiments of the present disclosure.

[0050] Referring to Fig. 5. The timestamp t1 represents the time of transmission of the sampling pulse signal; t1-t2 represents the time window in which the scattered light echo 1 generated by the sampling pulse signal is received; and t3-t4 represents the emission window in which the detection pulse signal is transmitted (e.g., the first time window or a second time window). If the detection pulse signal is transmitted at timestamp t3, t3-t4 represents the time window in which the scattered light echo 2 generated by the detection pulse signal is received; t1-t6 represents the time window 1 in which the sampling pulse signal is transmitted and the echo is received from the target object; t6-t5 represents the time window 2 for signal transmission and processing after receiving the echo from the target object; and t1-t5 represents the measurement time window.

[0051] The light transmitter can emit the detection pulse signal within the first time window t3-t4. This first time window t3-t4 is located at the end of the measurement time window t1-t5. The relative position between the first time window t3-t4 and the measurement time window t1-t5 is fixed and can be predefined. For example, the start timestamp t3 of the first time window t3-t4 can be predefined based on the timestamp t1 when the sampling pulse signal is emitted.

[0052] The first time window t3-t4 is located at the end of the measurement time window t1-t5. At this point, the echo from the target object may already have been received by the light receiver. The detection pulse signal can therefore be transmitted within the first time window t3-t4. The scattered light echo generated by the detection pulse signal cannot affect the reception of the echo from the target object. The scattered light echo cannot affect the detection of the target object by the LiDAR.

[0053] In some known methods, the intensity of the scattered light echo within the time window t1-t2 does not exceed the threshold thres1, whether an obstacle is present or absent, due to the use of scattered light reduction methods. The obstacle therefore cannot be detected. In the present disclosure, the detection pulse signal and the scanning pulse signal can be two independent pulse signals. Obstacle detection can be achieved without affecting the detection of the target object. Consequently, the scattered light echo generated by the detection pulse signal cannot be affected by the echo from the target object or by scattered light reduction methods. The accuracy of obstacle detection can be improved, ensured, or not diminished.

[0054] In some embodiments, in step 401 the detection pulse signal can be transmitted within a second time window that lies within the measurement time window. The second time window can be changed based on the reception time of an echo from the target object.

[0055] Referring to Fig. 5. The light source can transmit the detection pulse signal within the second time window t3-t4. The time at which the light receiver receives the complete echo from the target object is t6. The second time window t3-t4 can be modified based on the reception timestamp t6 of the echo from the target object. The light source can retransmit the detection pulse signal after the light receiver has received the echo from the target object. For example, the later the reception timestamp t6 of the echo from the target object, the later the start timestamp t3 of the second time window.

[0056] In some embodiments, the start timestamp t3 of the second time window t3-t4 can have a fixed offset from the received timestamp t6 of the echo from the target object. In some embodiments, the end timestamp t4 of the second time window t3-t4 can have a fixed offset from the received timestamp t6 of the echo from the target object.

[0057] In some embodiments, the first and second time windows represent a time window for detecting the obstacle. The duration of this time window can be shorter than the duration of the measurement time window. Furthermore, the durations of the first and second time windows can be shorter than the duration of either time window 1 or time window 2.

[0058] In some embodiments, the durations of the first and second time windows can be adjusted based on actual requirements, as long as the complete scattered light echo can be received, and this adjustment is not limited in the present disclosure. For example, the duration of the complete pulse width can be determined by counting the waveforms of different scattered light echoes from several LiDARs, and the longest duration is used.

[0059] In some embodiments, the measurement time window in step 401 can be divided into a first measurement time window and a second measurement time window. The first measurement time window can be configured to determine the flight time between the transmission of a sampling pulse signal for scanning a short-range target and the reception of an echo from the short-range target. The second measurement time window is configured to determine the flight time between the transmission of a sampling pulse signal for scanning a long-range target and the reception of an echo from the long-range target. Furthermore, the first measurement time window can comprise a time window 1 and a time window 2. Time window 1 is used for transmitting the sampling pulse signal and receiving the echo from the target. Time window 2 is used for signal transmission and processing after receiving the echo from the target. The second measurement time window can also comprise a time window 1 and a time window 2.

[0060] In some embodiments, the light transmitter can emit the detection pulse signal within the first measurement time window; and / or the light transmitter can emit the detection pulse signal within the second measurement time window. For example, the detection pulse signal is emitted at the end region within the first measurement time window and / or the second measurement time window.

[0061] In some embodiments, the LiDAR light emitter can transmit pulses using a dual-time-window method. The light emitter can transmit the scanning pulse signal for detecting a short-range target within the first measurement time window. The light emitter can transmit the scanning pulse signal for detecting a long-range target within the second measurement time window.

[0062] For example, the light source can transmit the scanning pulse signal within the first measurement time window using stray light reduction methods, thereby attenuating the stray light echo. To avoid or reduce the effect of the stray light reduction methods on the stray light echo, the light source can set the obstacle detection time window at the end of the first measurement time window for measuring the stray light echo. The light source can transmit the detection pulse signal at the end of the first measurement time window. Because the light intensity of the detection pulse signal is low, the detection pulse signal does not affect the distance measurement of the target object.

[0063] Fig. Figure 6 shows an exemplary schematic representation of a time window for sending a detection pulse signal according to some embodiments of the present disclosure. Fig.Figure 7 shows an exemplary schematic representation of another time window for sending a detection pulse signal according to some embodiments of the present disclosure.

[0064] In some embodiments, the LiDAR's light emitter can comprise multiple light emitter groups. Each light emitter group can comprise a plurality of light emitter channels. The plurality of light emitter channels can emit light sequentially. For example, the LiDAR comprises 8 light emitter groups (e.g., group AH). Each light emitter group comprises 16 light emitter channels. Referring to Fig. 6 and Fig. 7 corresponds to the temporal emission sequence of the 16 light transmitter channels, which in turn correspond to the time sequences 0 (e.g., “seq0” in Fig. 6 and Fig. 7) to time sequences 15 (e.g. “seq15” in Fig. 6 and Fig. 7) Loop0 represents the first measurement time window. Loop1 represents the second measurement time window.

[0065] In some embodiments, further referring to Fig. 6. Within the first measurement time window (Loop0), multiple light transmitter channels in each light transmitter group sequentially transmit a randomly coded sampling pulse signal of lower intensity based on a first time sequence (e.g., 0-seq0 to 0-seq15), thereby detecting a short-range target. Within the second measurement time window (Loop1), the multiple light transmitter channels in each light transmitter group sequentially transmit a randomly coded sampling pulse signal of higher intensity based on a second time sequence (e.g., 1-seq0 to 1-seq15), thereby detecting a long-range target. The randomly coded sampling pulse signal can be a sequence of pulse signals formed from a multitude of sampling pulse signals, such as a sequence of pulse signals derived from two sampling pulse signals.

[0066] The detection pulse signal can be emitted at the end of the first measurement window Loop0 of a preceding light transmitter channel of each light transmitter group, and before the start of the first measurement window Loop0 of a subsequent light transmitter channel of the same light transmitter group. For example, the detection pulse signal is used in Fig. 6. Time signaled by the dotted line.

[0067] In some embodiments, referring to Fig.7. Within the first measurement time window Loop0, a light transmitter channel in the light transmitter group AH emits a randomly coded sampling pulse signal of lower intensity, based on the first time sequence 0-seq0, to detect a short-range target. Within the second measurement time window Loop1, the light transmitter channel emits a sampling pulse signal of higher intensity, based on the second time sequence 1-seq0, to detect a long-range target. Similarly, within the first measurement time window Loop0, another light transmitter channel in the light transmitter group AH emits a randomly coded sampling pulse signal of lower intensity, based on the first time sequence 0-seq1.And a light transmitter channel in the light transmitter groups AH emits a sampling pulse signal with higher intensity within the second measurement time window Loop1 based on the second time sequence 1-seq1, until all light transmitter channels in the light transmitter groups AH have completed the specified emission time sequence.

[0068] The detection pulse signal can be emitted at the end of the first measurement window (Loop0) of each light transmitter channel and before the start of the second measurement window (Loop1). For example, the detection pulse signal is used to... Fig. 7. Time signaled by the dotted line.

[0069] Furthermore, the light emitter can also transmit the detection pulse signal within the second measurement time window, Loop1. If the LiDAR detects a short-range target object within the first measurement time window, Loop0, no sampling pulse signal needs to be transmitted within the second measurement time window, Loop1. The second measurement time window, Loop1, can be used as a time window for obstacle detection. The light emitter can transmit the detection pulse signal within the second measurement time window, Loop1.

[0070] Fig. Figure 8 shows an exemplary schematic representation of a further time window for sending a detection pulse signal according to some embodiments of the present disclosure.

[0071] In some embodiments, when the light transmitter sends the detection pulse signal as described above within the first measurement time window Loop0 or the second measurement time window Loop1, at least one light transmitter channel from each transmitter group can be randomly selected to send the detection pulse signal. This signal serves to detect whether an obstacle is present in the area of ​​the field of view for the corresponding transmitter groups. The result of the obstacle detection by one or more light transmitter channels can be used as the result of the obstacle detection for the entire transmitter group.

[0072] Referring to Fig.8. A light transmitter channel can be randomly selected from each transmitter group to transmit the detection pulse signal. For example, light transmitter channel 1 in transmitter group A can be selected to transmit the detection pulse signal at timestamp t0. Light transmitter channel 2 in transmitter group B can be selected to transmit the detection pulse signal at timestamp t1. Light transmitter channel 3 in transmitter group C can be selected to transmit the detection pulse signal at timestamp t2. Light transmitter channel m in transmitter group H can be selected to transmit the detection pulse signal at timestamp tm. The emission time sequence from light transmitter channel 1 to light transmitter channel m can be set in Fig. 8 should be represented as seq0-seqm.

[0073] In some embodiments, the light intensity of the detection pulse signal can be lower than the light intensity of the scanning pulse signal. The light intensity of the detection pulse signal can be lower relative to the scanning pulse signal. The detection pulse signal can be used for obstacle detection and not for measuring the distance to the target object. In some embodiments, the light intensity of the detection pulse signal only needs to meet the requirements for the intensity of the generated scattered light signal and the change (e.g., increase) of a feature parameter of the scattered light signal when an obstacle is present.

[0074] The light intensity of the detection pulse signal can be selected from a predefined light intensity range. The maximum value of the light intensity range can be determined by counting the light intensities of the detection pulse signals from a large number of LiDARs without obstacles, thus confirming the absence of an obstacle. The minimum value of the light intensity range can be determined by counting the light intensities of the detection pulse signals from a large number of LiDARs with an obstacle, which generate identifiable stray light signals. For example, the light intensity range can be predefined based on measurement results (such as tests conducted before the LiDARs are shipped or measurements taken during operation). A large number of initial LiDARs without obstacles are used for testing purposes.The light intensities of the detection pulse signals can be determined to their maximum value if no obstacle is detected by the first LiDARs. Similarly, a number of secondary LiDARs with at least one obstacle are used for testing purposes. The light intensities of the detection pulse signals can then be evaluated to their minimum value if no obstacle is detected by the secondary LiDARs.

[0075] Both the maximum and minimum values ​​mentioned above can be statistically determined under full temperature operating conditions (e.g., -40° to 120°) of the LiDAR.

[0076] Further referring to Fig. In step 403, the presence of an obstacle is determined based on a feature parameter of the scattered light techo. For example, the feature parameter of the scattered light techo can include at least one of the following quantities: pulse width, peak value, and integral value of the scattered light techo.

[0077] Fig. Figure 9 shows a schematic representation of exemplary feature parameters of a scattered light techos according to some embodiments of the present disclosure.

[0078] In some embodiments, with reference to Fig. Figure 9 shows the pulse width of the scattered light echo as W1 and the peak value of the scattered light echo as h1. The integral value of the scattered light echo represents the integral value of a scattered light echo signal within the timestamp t. The integral value corresponds to the area of ​​the scattered light echo, which is represented as E1.

[0079] In some embodiments, the presence of an obstacle is determined when the feature parameter of the scattered light technology reaches an obstacle detection threshold. Furthermore, different obstacle detection thresholds can be used for different feature parameters of the scattered light technology.

[0080] With regard to the feature parameter as the peak value of the scattered light techno, further referring to Fig. 5. When the peak value of the scattered light signal is reached, the obstacle detection threshold thres1 can be determined, thus establishing the presence of the obstacle. Similarly, when using the pulse width of the scattered light signal as a feature parameter, a corresponding obstacle detection threshold for the pulse width can be used. When using the integral value of the scattered light signal as a feature parameter, a corresponding obstacle detection threshold for the integral can be applied.

[0081] In some embodiments, the obstacle detection threshold can be determined by evaluating the differences between the feature parameters of the scattered light echoes of several radars with an obstacle and the feature parameters of the scattered light echoes of several radars without an obstacle, thereby setting the obstacle detection threshold in such a way that a distinction can be made between scattered light echoes with and without an obstacle.

[0082] In some embodiments, the obstacle detection threshold can be dynamically adjusted to changes in the environment in which the LiDAR is located. The obstacle detection threshold is dynamically modified based on changes in the environment where the LiDAR is deployed. For example, the obstacle detection threshold can be changed based on the temperature of the environment in which the LiDAR is located. The obstacle detection thresholds for different temperatures can be pre-defined and stored. In some examples, the obstacle detection threshold can be selected based on the temperature currently being measured in real time by a temperature sensor in the LiDAR.

[0083] In some embodiments, further referring to Fig.5. The LiDAR transmits the sampling pulse signal at timestamp t1 within the measurement time window and receives the echo from the target object at timestamp t6. The LiDAR transmits the detection pulse signal with lower intensity at timestamp t3 and receives the scattered light echo 2 within the time window t3-t4. If an obstacle is present, the peak value of the scattered light echo 2 exceeds the obstacle detection threshold thres1.

[0084] In contrast to the scattered light echo 1, which in the prior art is received within the time window t1-t2, the scattered light echo 2 described in the present disclosure can be unaffected by the echo of the target object or by means of scattered light reduction. The accuracy of obstacle detection can be improved, ensured, or not reduced.

[0085] Once the presence of the obstacle has been determined, the area in which the obstacle is located within the detection field of view can be further determined. For example, the area in which the obstacle is located on the light cover can be further determined.

[0086] In some embodiments, the area containing the obstacle can be determined based on a deviation in point cloud features between the first and second point cloud data sets. The first point cloud data sets are those acquired before the obstacle was detected. The second point cloud data sets are those acquired after the obstacle was detected. The deviation in point cloud features can include a distance deviation and / or a reflectance deviation.

[0087] In some embodiments, anomalous point cloud data can be determined in the second point cloud data based on the deviation of the point cloud features. The area in which the obstacle is located can be determined based on a scanning field of view of a scanning pulse signal that corresponds to the anomalous point cloud data.

[0088] In some embodiments, the emission pulse of each light source channel of the LiDAR can have a scanning field of view on the light cover. Each emission pulse can generate corresponding point cloud data. If an obstacle is present on the light cover, the corresponding light source channel can be determined based on the scanning field of view in which the obstacle lies on the light cover. Consequently, the point cloud data generated by the emission pulse of the light source channel will be anomalous. For example, distance or reflectance may be different. The anomalous point cloud data can be identified by comparing the normal point cloud data (e.g., the first point cloud data) before the obstacle appeared with the second point cloud data after the obstacle appeared.The scanning field of view of the emission pulse, which corresponds to the anomalous point cloud data, can represent the area in which the obstacle is located.

[0089] In some implementations, the area containing an obstacle can be determined based on several consecutive frames of point clouds. If the obstacle is identified within the same area, its presence in that area is confirmed. This can improve or ensure the robustness of obstacle detection.

[0090] In some embodiments, the area containing the obstacle can also be determined based on the vertical position of the light source channel emitting the detection pulse signal, as well as the associated horizontal field of view of that light source channel. The number of regions can be one or more. The horizontal field of view (FOV) of each light source channel in the LiDAR can be determined based on the azimuth angle of the multifaceted rotating mirror.

[0091] The area containing the obstacle can include both a vertical and a horizontal position. The vertical position can be determined based on the position of a group of light sources in the vertical direction within the light source groups. The horizontal position can be determined based on the horizontal field of view.

[0092] In some embodiments, the LiDAR can include multiple groups of light emitters. The scanning field of view of the light coverage can be divided into multiple intervals vertically by the multiple light emitter groups. The scanning field of view of the light coverage can also be divided into multiple intervals horizontally by multiple horizontal viewing angles. If an obstacle is detected, a portion of the obstacle can be determined based on the light emitter channel from which the detection pulse signal was emitted and which detected the obstacle.

[0093] Fig. Figure 10 shows a schematic representation of an exemplary area division according to some embodiments of the present disclosure. In some embodiments, the LiDAR comprises eight light emitter groups 81, referring to Fig.10. The scanning field of view of the light cover 80 is divided into eight vertical intervals by the eight light emitter groups 81. The horizontal field of view is 0–120 degrees with a granularity of 10 degrees. The scanning field of view of the light cover 80 is divided into 12 intervals in the horizontal direction. When the presence of an obstacle is determined based on the scattered light echo, the detection pulse signal associated with the scattered light echo can first be determined. A vertical interval can be determined based on the light emitter group to which the light emitter channel that emitted the detection pulse signal belongs. Similarly, a horizontal interval can be determined based on the horizontal field of view of the light emitter channel.

[0094] In some embodiments, the light transmitter channel that emits the detection pulse signal can be at least one light transmitter channel in the transmitter group. The result of the obstacle detection by the at least one light transmitter channel can be used as the result of the obstacle detection for the entire transmitter group. The result of the obstacle detection by the at least one light transmitter channel can also be used as the detection result to determine whether an obstacle is present in the scanning field of view of the entire transmitter group.

[0095] Using Table 1 as an example, an obstacle can be determined to be present in the area formed by the light source group containing channels 32-47 and horizontal field-of-view angles of 20.1-30 degrees, the area formed by the light source group containing channels 48-63 and horizontal field-of-view angles of 20.1-30 degrees, the area formed by the light source group containing channels 32-47 and horizontal field-of-view angles of 30.1-40 degrees, and the area formed by the light source group containing channels 48-63 and horizontal field-of-view angles of 30.1-40 degrees. Table 1 0-10 10,1-20 20,1-30 30,1-40 ... 90,1-100 100,1-110 Channels 0-15 Channels 16-31 Channels 32-47 Obstacle present Obstacle present Channels 48-63 Obstacle present Obstacle present ... Channels 112-127

[0096] In some embodiments, the multitude of areas in which the specific obstacle is located can be counted. If the multitude of areas is spatially sequential, it is confirmed that the obstacle is present in the multitude of areas. For example, if dirt is detected on the light cover, it is assumed that dirt is present on the light cover at three consecutive intervals. This can reduce or prevent false detections. The accuracy of obstacle detection can be improved or ensured.

[0097] In some embodiments, the stray light signals can be echoes corresponding to the detection pulse signals emitted by multiple light source channels in multiple light source groups. The number of first light source channels whose associated stray light signals reach the obstacle detection threshold in each light source group can be counted. When the number of first light source channels in the same light source group reaches a first threshold, the presence of an obstacle is determined. For example, each light source group comprises 16 light source channels. When the number of first light source channels whose stray light signals reach the obstacle detection threshold reaches 8, the presence of an obstacle can be determined. False detection can thus be reduced or avoided. The accuracy of obstacle detection can be improved or ensured.

[0098] Once the presence of an obstacle has been determined, its type can also be further specified. The obstacle can be either permeable or impermeable. The pulse signal can pass through a permeable obstacle but not an impermeable one. For example, permeable obstacles can include transparent, refractive, and scattering obstacles. Impermeable obstacles can include absorbing and reflecting obstacles.

[0099] The impermeable obstacle may include asphalt, paint, dust, dirt or similar substances, and the permeable obstacle may include scratches, gravel pits, insect bodies, bird droppings, greasy sweat, fingerprints, sewage, clear water or similar substances, which are not exhaustively listed here.

[0100] Fig.Figure 11 shows a schematic representation of the energy of a sampling pulse signal from a laser according to some embodiments of the present disclosure. Referring to Fig. Q1 represents the laser emission energy. Q2 represents the laser energy consumed internally, and Q3 represents the laser energy reflected by a reflecting obstacle. Q4 represents the laser energy absorbed by an absorbing obstacle. Q5 represents the laser energy scattered by a scattering obstacle. Q6 represents the laser energy refracted by a refractive obstacle. Q7 represents the laser energy transmitted by a transparent obstacle. Q6 represents the laser energy received by the light receiver.

[0101] In some embodiments, different obstacle detection thresholds can be determined for different types of obstacles. For example, two types of the obstacles mentioned above can be defined. The degree of influence of these two types of obstacles on the change (e.g., increase) of the stray light techo can be determined. Two mean values ​​can be determined, for example, a first obstacle detection threshold and a second obstacle detection threshold.

[0102] For example, when the first obstacle detection threshold is reached, the feature parameter of the scattered light techno determines that a first obstacle is present and that the first obstacle is a permeable obstacle. When the second obstacle detection threshold is reached, the feature parameter of the scattered light techno determines that a second obstacle is present and that the second obstacle is an impermeable obstacle.

[0103] Fig. Figure 12 shows an exemplary schematic representation of pulse signals with different types of obstacles according to some embodiments of the present disclosure. In some embodiments, referring to Fig. 12. The second obstacle detection threshold is higher than the first obstacle detection threshold. The first obstacle detection threshold can distinguish between the scattered light echo without an obstacle and the scattered light echo with a transparent obstacle. The second obstacle detection threshold can distinguish between the scattered light echo with a transparent obstacle and the scattered light echo with an opaque obstacle.

[0104] Different types of obstacles affect the point cloud data differently, with the types of obstacles reflecting the degree of blockage or the degree of contamination. For example, the degree of blockage may be higher for an impermeable obstacle than for a permeable obstacle.

[0105] Fig. Figure 13 shows a further exemplary schematic representation of pulse signals with different types of obstacles according to some embodiments of the present disclosure. Referring to Fig. 13. The effects of the absorbing and reflecting barriers on the echo from the target object are strongest. The blocking levels of these two types of obstacles are more pronounced. The effects of the transparent, scattering, and refractive barriers on the echo from the target object are less pronounced. The blocking levels of these three types of obstacles are lower.

[0106] In some embodiments, when determining the presence of an obstacle, the number of first light transmitter channels corresponding to stray light signals that reach the obstacle detection threshold can be counted in each light transmitter group. The degree of obstruction caused by the obstacle can be determined based on the number of first light transmitter channels.

[0107] In some embodiments, the greater the number of first light emitter channels in a light emitter group, the greater the degree of obstacle blockage within the scanning field of view corresponding to that light emitter group. For example, each light emitter group comprises 16 light emitter channels. If the number of first light emitter channels corresponding to stray light signals reaching the obstacle detection threshold is 12 in a light emitter group, the degree of obstacle blockage within the scanning field of view corresponding to that light emitter group is higher than in a light emitter group where the number of first light emitter channels corresponding to stray light signals reaching the obstacle detection threshold is 10.

[0108] In some embodiments, an alarm message can be issued when the presence of an obstacle is detected.

[0109] The alarm message can be used to indicate one or more of the following: the presence of an obstacle, the area where the obstacle is located, the type of obstacle, and control information. The control information can be used to control the LiDAR or a device mounted on the LiDAR.

[0110] In some embodiments, if the obstacle type is an impermeable barrier and the area containing the obstacle is large, the point cloud data acquired at that time may be considered unreliable. Control information can be output. The LiDAR input to the vehicle detection system can be controlled and shut down based on this information. The LiDAR can be detected and controlled so that it does not send erroneous point cloud data to the vehicle detection system based on this information.

[0111] In some embodiments, control information can also be output in the event of a severe level of obstruction, in order to control the execution of a faulty action. For example, a vehicle with a LiDAR is traveling at high speed. A braking or deceleration action can be initiated while the LiDAR is switched off if an alarm message is received.

[0112] The obstacle detection method described above can be performed by a LiDAR. For example, the individual steps of the method described above can be executed by a processor integrated into the LiDAR. Alternatively, the individual steps of the method described above can be performed by an end device connected to the LiDAR. This end device could be a processor, a controller, a vehicle, a drone, or a robot.

[0113] The serial numbers of the respective steps in the embodiments of this disclosure do not serve to restrict the execution order of the steps. The steps can be executed in parallel or separately.

[0114] In some embodiments, the obstacle detection method can be implemented by means of a software program, wherein the software program is executed in a processor integrated into a chip or chip module. The method can also be implemented by means of a combination of software and hardware, which is not limited by the present application.

[0115] Fig. Figure 14 shows a schematic structural representation of an example device for detecting an obstacle according to some embodiments of the present disclosure. Referring to Fig.14. A device for dirt detection of the light cover 120 can include a control module 1201 and a detection module 1202.

[0116] The 1201 control module can control the transmission of a detection pulse signal within a measurement time window and monitor the reception of a corresponding stray light echo. The measurement time window can be configured to determine the flight time between the transmission of a scanning pulse signal to detect a target object and the reception of an echo from the target object.

[0117] The detection module 1202 can determine whether an obstacle is present based on a feature parameter of the scattered light techos.

[0118] In some embodiments, the control module may include a controller, a control circuit, a processor, a processor circuit, or other hardware components for control. For example, the module may include a processor (e.g., a digital signal processor, microcontroller, FPGA, central processing unit, application-specific integrated circuit, or similar) and a computer program, wherein the module's function is realized on the processor when the computer program is executed. The computer program may be stored in memory (e.g., random-access memory (RAM), flash memory, read-only memory (ROM), programmable ROM, registers, hard disk, removable disk media, or some other form of storage medium) or on a server. The detection module may include a processor, a processor circuit, a controller, a control circuit, or other hardware components for detection.For example, the detection module can include a processor and a computer program, with the function of the detection module being implemented on the processor when the computer program is executed.

[0119] In some embodiments, the control module 1201 can control the light transmitter to send the detection pulse signal within a first time window at the end of the measurement time window. The control module 1201 can also control the light transmitter to send the detection pulse signal within a second time window. This second time window lies within the measurement time window. The second time window can be changed based on the reception time of the echo from the target object.

[0120] In some embodiments, the control module 1201 can control the light transmitter to send the detection pulse signal within a first measurement time window. The first measurement time window is configured such that a flight time is determined between the transmission of a scanning pulse signal for detecting a short-range target object and the reception of an echo from the short-range target object.

[0121] In some embodiments, the control module 1201 can control the light transmitter to send the detection pulse signal within a second measurement time window. The second measurement time window is configured to determine a flight time between the transmission of a scanning pulse signal to scan a long-range target object and the reception of an echo from the long-range target object.

[0122] For further details on the operating principle and working mode of the 120 obstacle detection device, please refer to the corresponding descriptions in Fig. 4 to Fig. Reference is made to paragraph 13 and the corresponding embodiments. The details are not repeated here.

[0123] In some embodiments, the obstacle detection device may be a chip with obstacle detection functionality in a LiDAR or a terminal device, such as a system-on-a-chip (SoC), a baseband chip, or similar. Alternatively, the obstacle detection device may comprise a module with a chip that provides obstacle detection functionality in a LiDAR or terminal device. Or the obstacle detection device may be a chip module with a functional data processing chip. Or the obstacle detection device may be a LiDAR or a terminal device.

[0124] Fig. Figure 15 shows an exemplary schematic structural representation of a LiDAR according to some embodiments of the present disclosure. Referring to Fig.15. The LiDAR comprises at least one light transmitter 1301 and at least one light receiver 1302. The LiDAR can transmit a scanning pulse signal or a detection pulse signal via the light transmitter 1301. The light receiver 1302 can receive an echo of the scanning pulse signal reflected by the target object 1303. Or the light receiver 1302 can receive a scattered light echo of the detection pulse signal reflected by the obstacle 1304.

[0125] In addition, at least one light transmitter 1301 can be assigned to each light receiver 1302.

[0126] The respective modules / units in the respective devices and products described in the embodiments can be software modules / units, hardware modules / units, or partly software modules / units and partly hardware modules / units. For example, in devices and products integrated into or applied to a chip, the modules / units contained therein can be implemented by hardware such as circuits, or at least some of the modules / units can be implemented by a software program executed on a processor integrated into the chip, with the remaining modules / units, if any, being implemented by hardware such as circuits; in devices or products integrated into or applied to a chip module, the modules / units contained therein can be implemented by hardware such as circuits, with different modules / units in the same component (e.g.,The modules / units are arranged in the same component (e.g., chip, circuit module, etc.) or in different components of the chip module, or at least some modules / units are implemented by a software program executed on a processor integrated in the chip module, and the remaining modules / units, if any, are implemented by hardware such as circuits; in devices or products that are integrated into or applied to an end device, the modules / units contained therein may be implemented by hardware such as circuits, wherein different modules / units are arranged in the same component (e.g., chip, circuit module, etc.) or in different components in the end device, or at least some of the modules / units are implemented by a software program executed on a processor integrated in the end device, and the remaining modules / units, if any, are implemented by hardware such as circuits.

[0127] The present disclosure further discloses a storage medium. The storage medium is a computer-readable storage medium with a computer program stored on it that can perform the steps of the method described above. The storage medium may comprise read-only memory (ROM), random-access memory (RAM), a magnetic hard disk, or a CD. The storage medium may further comprise non-volatile memory or non-transient memory.

[0128] The disclosure further discloses an end device. The end device may comprise memory and a processor. The memory contains a computer program stored thereon, which is executable on the processor. When executing the computer program, the processor can perform the steps of the procedure described above. Optionally, the end device includes one of the obstacle detection devices described above and / or the LiDAR.

[0129] The terms "or" and "and / or" in this disclosure describe a relationship of association between associated objects and constitute a non-exclusive inclusion. For example, each of "A and / or B" and "A or B" can include: only "A" exists, only "B" exists, and "A" and "B" both exist, where "A" and "B" can be singular or plural. By another example, each of "A, B and / or C" and "A, B, or C" can include: only "A" exists, only "B" exists, only "C" exists, "A" and "B" both exist, "A" and "C" both exist, "B" and "C" both exist, and "A," "B," and "C" all exist, where "A," "B," and "C" can be singular or plural. Additionally, the symbol " / " here indicates that the associated objects before and after the sign are in an "or" relationship.

[0130] The terms “a multitude of” and “several” in this revelation refer to a number of at least two. For example, several objects may comprise two objects or more than two objects.

[0131] The terms "first", "second", or the like in this disclosure serve only to illustrate and distinguish the described objects. The terms "first", "second", or the like in the embodiments of this disclosure do not signify any particular order, nor do they represent a specific limitation on the number of devices described in this disclosure, and are not restrictive.

[0132] The term “connection” in the present disclosure includes various connection methods such as direct or indirect connections that enable communication between devices and does not limit the present disclosure.

[0133] In some embodiments, the processor can be a central processing unit (CPU). The processor can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), another programmable logic device, a discrete gate, a transistor logic device, or a discrete hardware component. The general-purpose processor can be a microprocessor or any conventional processor.

[0134] It is understood that the memory of this disclosure may be volatile or non-volatile memory, or may comprise both. The non-volatile memory may be a ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), or flash memory. The volatile memory may be RAM used as an external cache. For illustration, but not as a limitation, various types of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-rate SDRAM (DDR SDRAM), extended SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct Rambus RAM (DR RAM).

[0135] The embodiments described above can be implemented wholly or partially in software, hardware, firmware, or any combination thereof. When implemented in software, the embodiments described above can be realized wholly or partially in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, they generate, in whole or in part, methods or functions according to the present disclosure. The computer can be a general-purpose computer, a specialized computer, a computer network, or any other programmable device.Computer instructions can be stored on a computer-readable storage medium or transferred from one computer-readable storage medium to another, for example, by wired or wireless transmission from one website, computer, server, or data center to another. The computer-readable storage medium can be any available medium that a computer can access, or a data storage device such as a server or data center that contains one or more collections of available media.It is to be understood that in various embodiments of the present application the consecutive numbers of the preceding processes do not signify an execution order and that the execution order of the preceding processes is to be determined on the basis of their functions and internal logic, whereby this does not constitute a restriction for implementation processes of the present disclosure.

[0136] In the various embodiments of the present application, it is understood that the methods, devices, and systems disclosed herein can also be implemented in other ways. For example, the devices in the embodiments described above are only exemplary; for example, the division of the units represents merely a logical subdivision, which can also be carried out differently in the actual implementation; for example, different units or components can be combined or integrated into another system, or certain features can be omitted or not implemented. Furthermore, the related or discussed coupling or direct coupling or communication link can be an indirect coupling or communication link through interfaces, devices, or units, which can be electrical, mechanical, or in another form.

[0137] The components depicted as separate units may be physically separate or not, and the components depicted as units may be physical or non-physical units. The units may be located in one place or distributed across a multitude of network units. Some or all of these units may be selected based on practical requirements to achieve the objectives of the solutions described here.

[0138] Furthermore, various functional units can be integrated into a single processing unit in the respective embodiments of the application; each unit can be physically separate, or two or more units can be combined into one. The integrated unit described above can be implemented in the form of hardware or as a combination of hardware and software functional units.

[0139] The integrated unit described above, implemented as a software functional unit, can be stored on a computer-readable storage medium. The software functional unit described above is stored on a storage medium and contains a set of instructions to enable a computer device (which may be a personal computer, a server, or a network device) to execute some of the steps of the method described in various embodiments of the application.

[0140] Although the present disclosure has been presented above, it is not limited thereto. Skilled workers may make various changes and modifications without departing from the spirit and scope of the present disclosure; therefore, the scope of protection of the disclosure is subject to the extent defined by the subsequent claims. QUOTES INCLUDED IN THE DESCRIPTION

[0000] This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited patent literature

[0000] CH 202211566326.1

[0001]

Claims

[1] Method for detecting an obstacle for a LiDAR, comprising: Emitting a detection pulse signal to scan the obstacle within a measurement time window, wherein the measurement time window is configured to determine a flight time between the emission of a scanning pulse signal to scan a target object and the reception of an echo from the target object; Receiving a scattered light signal corresponding to the detection pulse signal; and Determine whether the obstacle is present based on a feature parameter of the scattered light techos. [2] The method of claim 1, wherein determining whether the obstacle is present based on a feature parameter of the scattered light techos comprises: When the feature parameter of the scattered light techo reaches an obstacle detection threshold, determine that the obstacle is present, where the feature parameter of the scattered light techo includes at least one of the following quantities: pulse width, peak value, and integral value of the scattered light techo. [3] Method according to claim 2, wherein the obstacle detection threshold is determined in advance by counting the feature parameters of scattered light techos of a plurality of LiDARs with an obstacle and feature parameters of the scattered light techos of the plurality of LiDARs without an obstacle. [4] Method according to claim 2 or 3, wherein the obstacle detection threshold is dynamically changed based on changes in the environment of the LiDAR. [5] Method according to any one of claims 1 to 4, wherein the emission of the detection pulse signal within a measurement time window comprises the following: Emitting the detection pulse signal within a first time window; or Emitting the detection pulse signal within a second time window; where the first time window lies in an end region within the measurement time window, the second time window is located within the measurement time window, and the second time window is modified based on a reception time of the echo from the target object. [6] Method according to any one of claims 1 to 5, wherein the measurement time window comprises a first measurement time window and a second measurement time window, and the sending of the detection pulse signal within a measurement time window comprises the following: Transmitting the detection pulse signal within the first measurement time window, wherein the first measurement time window is configured to determine a flight time between the transmission of a sampling pulse signal to scan a short-range target object and the reception of an echo from the short-range target object; and / or Emitting the detection pulse signal within the second measurement time window, wherein the second measurement time window is configured to determine a flight time between the emission of a sampling pulse signal to scan a long-range target object and the reception of an echo from the long-range target object. [7] Method according to any one of claims 1 to 6, wherein the duration of a time window to the scanning obstacle is shorter than the duration of the measurement time window. [8] Method according to any one of claims 1 to 7, wherein the light intensity of the detection pulse signal is less than the light intensity of the scanning pulse signal. [9] Method according to any one of claims 1 to 8, wherein the light intensity of the detection pulse signal is selected from a light intensity range, a maximum value of the light intensity range is determined by counting the light intensities of detection pulse signals of a plurality of LiDARs without an obstacle, based on a determination that no obstacle is present, and a minimum value of the light intensity range is determined by counting the light intensities of detection pulse signals that produce identifiable stray light techos of the plurality of LiDARs with the obstacle. [10] Method according to any one of claims 1 to 9, further comprising: Determining an area in which the obstacle is located based on a deviation in point cloud features between first point cloud data and second point cloud data, wherein the first point cloud data are point cloud data collected before the obstacle was detected, the second point cloud data are point cloud data collected after the obstacle was detected, and the deviation in point cloud features includes a distance deviation and / or a reflectance deviation. [11] Method according to claim 10, wherein determining an area in which the obstacle is located based on a deviation of point cloud features between first point cloud data and second point cloud data comprises: Determining abnormal point cloud data in the second point cloud dataset based on the deviation of the point cloud features; and Determining the area where the obstacle is located, based on a scanning field of view area of ​​a scanning pulse signal that corresponds to the abnormal point cloud data. [12] Method according to claim 10 or claim 11, further comprising: Determine that an obstacle exists in an area if the obstacle, determined based on a multitude of successive frames of point clouds, is located in one and the same area. [13] Method according to any one of claims 1 to 12, further comprising: Determining an area in which the obstacle is located, based on a position where a light transmitter channel emitting the detection pulse signal is located in a vertical direction and within a horizontal field of view corresponding to the light transmitter channel. [14] The method of claim 13, wherein the area in which the obstacle is located comprises a vertical position and a horizontal position, and determining an area in which the obstacle is located based on a position where a light transmitter channel emitting the detection pulse signal is located in a vertical direction and in a horizontal field of view corresponding to the light transmitter channel comprises: Determining the vertical position based on the position of a group of light emitters containing the light emitter channel in the vertical direction; and Determining the horizontal position based on the horizontal field of view. [15] Method according to claim 10 or 13, further comprising: Counting a large number of areas where a particular obstacle is located; and Determine that the obstacle is present in the multitude of areas if the multitude of areas are spatially contiguous. [16] Method according to any one of claims 1 to 15, wherein the scattered light echoes are echoes corresponding to the detection pulse signals emitted by a plurality of light transmitter channels in a plurality of light transmitter groups, the method further comprising: Counting a number of first light emitter channels corresponding to the scattered light techos that reach an obstacle detection threshold for obstacle identification in each light emitter group; and Determine that the obstacle is present when the number of first light transmitter channels in the same light transmitter group reaches a first threshold. [17] Method according to any one of claims 1 to 16, wherein determining whether an obstacle is present based on a feature parameter of the scattered light techos comprises: Determine that a first obstacle is present when the feature parameter of the scattered light techos reaches a first obstacle detection threshold, where one type of first obstacle is a permeable obstacle; or Determine that a second obstacle is present when the feature parameter of the scattered light techos reaches a second obstacle detection threshold, where one type of the second obstacle is an impermeable obstacle and the second obstacle detection threshold is greater than the first obstacle detection threshold. [18] Method according to any one of claims 1 to 17, wherein the scattered light echoes are echoes corresponding to the detection pulse signals emitted by a plurality of light transmitter channels in a plurality of light transmitter groups, the method further comprising: Counting a number of first light emitter channels corresponding to stray light techos that reach an obstacle detection threshold in each light emitter group when it is determined that the obstacle is present; and Determining the type of obstacle based on the number of the first light transmitter channels. [19] Method according to any one of claims 1 to 18, further comprising: Output of alarm information when it is determined that the obstacle is present, wherein the alarm information is used to indicate one or more of the following: presence of the obstacle; an area in which the obstacle is located; a type of obstacle; and control information, wherein the control information is used to control the LiDAR or a device mounted on the LiDAR. [20] Device for detecting an obstacle for a LiDAR, comprising: a control module configured to control the emission of a detection pulse signal for scanning an obstacle within a measurement time window and to control the reception of a stray light echo corresponding to the detection pulse signal, wherein the measurement time window is configured to determine a flight time between the emission of a scanning pulse signal for detecting a target object and the reception of an echo from the target object; and a determination module configured to determine whether an obstacle is present based on a feature parameter of the scattered light techos. [21] A computer-readable storage medium with a computer program stored thereon, wherein the computer program, when executed by a computer, performs the steps of the method according to any one of claims 1 to 19. [22] LiDAR, comprehensive: a light transmitting device configured to emit a scanning pulse signal for scanning a target object and a detection pulse signal for detecting an obstacle; a light receiving device configured to receive an echo generated by the scanning pulse signal across the target object and a scattered light echo corresponding to the detection pulse signal; and a controller with a computer program stored thereon, wherein the controller, when executing the computer program, performs the steps of the method according to any one of claims 1 to 19.

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