Object recognition by active optical sensor system

Abstract

According to a method for object recognition by means of an active optical sensor system (2), a detector unit (2b) detects light (3b) reflected from an object (4) and generates a sensor signal (5a, 5b, 5c, 5d, 5e, 5f) on the basis thereof. A computing unit (2c) determines, for the amplitude of the sensor signal (5a, 5b, 5c, 5d, 5e, 5f), a first pulse width (D1) defined by a predetermined first limit value (G1) and a second pulse width (D2) defined by a predetermined second limit value (G2). According to at least one predefined signal pulse parameter, a signal pulse is assigned to one of at least two categories, and a scatter plot for object recognition is generated, which contains exactly one entry for the signal pulse, which corresponds to the first pulse width (D1) or the second pulse width (D2) depending on the category to which the signal pulse belongs.

Description

Technical Field

[0001] This invention relates to a method for object recognition using an active optical sensor system, wherein reflected light in the environment of the sensor system is recorded by means of a detector unit of the sensor system and an object, and a sensor signal is generated based on the recorded light. A first pulse width of the signal pulse of the sensor signal is determined by means of a computer unit, the first pulse width being established by a predetermined first limit value of the amplitude of the sensor signal. The invention also relates to a method for at least partial automatic control of a motor vehicle, an active optical sensor system, an electronic vehicle guidance system for a motor vehicle, a computer program, and a computer-readable storage medium. Background Technology

[0002] Active optical sensor systems, such as lidar systems, can be installed on motor vehicles to perform various functions of electronic vehicle guidance systems or driver assistance systems. These functions include distance measurement, distance control algorithms, lane keeping assist systems, object tracking, object recognition, and object classification.

[0003] In this case, the detected light results in an analog signal pulse, which has a time curve reproducing the intensity of the detected light. To represent this information discretely, the signal pulse can be described, for example, by a specific pulse width defined by the time the pulse is above a certain limit value.

[0004] In this context, the choice of the limiting value used to determine the pulse width typically affects various qualitative aspects of the resulting point cloud. A larger limiting value results in a lower sensitivity or effective range for the active optical sensor system, as the typical maximum amplitude of the sensor signal decreases with increasing distance from the sensor system. If the limiting value is therefore chosen too high, only objects relatively close to the sensor system tend to be reproduced in the point cloud. On the other hand, when the limiting value is chosen low, the effect of noise becomes quite significant. At very low limiting values, signal pulses that do not correspond to reflections from real objects in the sensor system's environment may also result in entries in the point cloud.

[0005] Document EP 1 557 694 B1 describes a method for classifying objects. In this case, a laser scanner is used to sample the environment of a motor vehicle, and the echo pulse width of the received reflected light pulses is evaluated. A threshold that the light pulse must exceed is defined, and the time difference from exceeding the threshold until it subsequently falls below the threshold is defined as the echo pulse width of the light pulse. Summary of the Invention

[0006] In this context, the object of the present invention is to provide an improved concept for object recognition using an active optical sensor system, in which the effects of noise can be reduced or kept to a minimum, while the sensitivity of the sensor system can be increased or kept constant.

[0007] According to the invention, this objective is achieved by the corresponding subject matter of the independent claims. Advantageous modifications and further configurations are the subject matter of the dependent claims.

[0008] The improved concept is based on the idea that a mixed point cloud is generated by identifying at least one of two categories for each signal pulse, and an entry for the signal pulse is generated in the point cloud according to the category, which corresponds to a first pulse width or a second pulse width of the signal pulse, with different pulse widths corresponding to different limits of the amplitude of the sensor signal.

[0009] According to an improved concept, a method for object recognition using an active optical sensor system, particularly a motor vehicle or an active optical sensor system for a motor vehicle, is provided. Light reflected by an object in the environment of the sensor system is recorded by a detector unit of the sensor system, and a sensor signal is generated based on the recorded light by the detector unit. A first pulse width of the signal pulse of the sensor signal is determined by a computer unit, particularly a computer unit of the sensor system or the motor vehicle, and the first pulse width is established by a predetermined first limit value of the amplitude of the sensor signal. A second pulse width of the signal pulse is determined by the computer unit, and this second pulse width is established by a predetermined second limit value of the amplitude of the sensor signal, which is particularly different from the first limit value. Based on at least one predetermined parameter of the signal pulse, the signal pulse is assigned to one of at least two predetermined categories, particularly exactly one, by the computer unit. A point cloud for object recognition is generated by the computer unit, the point cloud containing exactly one signal pulse entry. Depending on the category of the signal pulse, i.e., the category to which the signal pulse is assigned, this entry corresponds to either the first pulse width or the second pulse width.

[0010] Herein and below, an active optical sensor system can be defined as a system having an emitter unit with a light source, particularly for emitting light, for example, in the form of light pulses. Specifically, the light source can be configured as a laser. Furthermore, the active sensor system has a detector unit having at least one optical detector, particularly for recording light or light pulses, especially the reflected component of the emitted light.

[0011] Here and below, the term "light" can be understood as electromagnetic waves encompassing the visible, infrared, and / or ultraviolet ranges. Therefore, the term "optical" can also be understood in this sense as related to light.

[0012] Light emitted by an active optical sensor system can, in particular, include infrared light, for example, with wavelengths of 905 nm, approximately 905 nm, 1200 nm, or approximately 1200 nm. In this case, these wavelength specifications can each relate to a wider range of wavelengths, which is typical of the corresponding light source.

[0013] In current active optical sensor systems, the light source can be, for example, a laser source. Within conventional tolerances, the wavelength mentioned can correspond to, for example, the peak wavelength of a laser spectrum.

[0014] Specifically, light is emitted in the direction of the object by means of the transmitter unit of the sensor system, and the recorded reflected light includes the component of the emitted light reflected by the object.

[0015] A point cloud can be understood, for example, as a set of data points with multiple entries, each entry corresponding to a specific signal pulse from a sensor signal generated by a detector unit. In this case, if the sensor signal contains multiple signal pulses (also called echoes), various different entries may originate from the same sensor signal. However, each entry is precisely assigned to a single signal pulse.

[0016] Each entry may, for example, contain multiple parameters or attributes, or other information items for the corresponding signal pulse. For instance, an entry may contain the two-dimensional or three-dimensional coordinates of a corresponding point in the environment from which light is reflected and, after being recorded by the detector unit, results in a corresponding signal pulse. For example, the coordinates may be in polar or Cartesian coordinate form. The entry may also contain the echo number of the corresponding signal pulse. The echo number then corresponds, for example, to the corresponding position of the signal pulse within a series of consecutive signal pulses in the same sensor signal.

[0017] Furthermore, this entry can, in principle, contain information related to the pulse width or maximum signal amplitude of the signal pulse. However, according to the improved concept, each entry in the point cloud precisely contains a value related to the pulse width, that is, either the value of the first pulse width or the value of the second pulse width, but not both.

[0018] However, a single signal pulse or various different signal pulses may not generate an entry.

[0019] The entry corresponding to the first or second pulse width can be understood as meaning that the entry contains a value proportional to or equal to the first or second pulse width. A point cloud precisely containing one entry of a signal pulse is, in particular, understood to mean that the point cloud does not contain other entries of the same signal pulse. However, of course, a point cloud may contain other entries of other signal pulses belonging to the same sensor signal or another sensor signal.

[0020] This point cloud can be used by this computer unit or other computer units for object recognition, that is, specifically for object classification. Therefore, this point cloud can be referred to as a point cloud for object recognition.

[0021] Based on the improved concept, as described above, different extreme values ​​of pulse width or signal amplitude are used depending on the parameters of the signal pulse. On the one hand, this prevents pulse signals that do not correspond to reflections of real objects, but rather appear due to noise, from being considered in further processing of the point cloud. However, at the same time, it achieves the effect that the most unlikely signal pulses due to real reflections of real objects are ignored.

[0022] In other words, in this way, the impact of noise effects is reduced on the one hand, which corresponds to higher reliability of object recognition based on the improved concept, and on the other hand, the sensitivity or effective range of the sensor system is high.

[0023] Furthermore, this method based on the improved concept saves storage space for storing point clouds because it contains only one entry for each signal pulse. If two point clouds are generated, for example, one for a first limit value and the corresponding first pulse width, and one for a second limit value and the corresponding second pulse width, the storage requirements will be significantly higher. This is also particularly applicable when entries contain corresponding information items associated with a specified category, such as flags or identifiers.

[0024] According to at least one embodiment of the method based on the improved concept, the radial distance of an object from the sensor system is determined by means of a computer unit based on signal pulses. The signal pulses are then assigned to one of at least two categories based on the radial distance using the computer unit.

[0025] For example, in this case, the radial distance can be determined by the time of flight (ToF). The longer the duration between the emission of the emitted light and the detection of the corresponding signal pulse, the longer the time of flight, and the greater the corresponding radial distance.

[0026] Radial distance is particularly suitable as a parameter for signal pulse classification because the likelihood of a signal pulse exceeding a certain amplitude decreases as the radial distance increases. In other words, the maximum amplitude of the signal pulse decreases as the radial distance increases. Therefore, it is meaningful to use a low limiting value to determine the pulse width for large radial distances and a high limiting value for smaller radial distances, especially to reduce the effects of noise.

[0027] Specifically, if the radial distance is greater than a predetermined limit distance, the signal pulse can be assigned to the first category of at least two categories. On the other hand, if the radial distance is less than the limit distance, the signal pulse can be assigned to the second or third category of at least two, and optionally at least three, categories.

[0028] According to at least one embodiment, the second limit value is greater than the first limit value.

[0029] According to at least one embodiment, if the radial distance is greater than a predetermined limit distance, a signal pulse is assigned to a first category of at least two categories by means of a computer unit. If the signal pulse has already been assigned to the first category, a point cloud is generated by means of the computer unit using entries corresponding to the width of the first pulse.

[0030] In such an embodiment, the radial distance corresponds to one of the parameters of the signal pulse.

[0031] If the radial distance is greater than the limit distance, the probability of no signal pulse due to noise can be considered high. Therefore, it is advantageous to consider a lower first limit value and a corresponding first pulse width for generating the point cloud, so that objects can be represented as far as possible in the point cloud. As a result, the sensitivity of the optical sensor system is increased.

[0032] According to at least one embodiment, if the radial distance is less than the limit distance and the second pulse width is greater than zero, the signal pulse is assigned to the second category of at least two categories, particularly by means of a computer unit. If the signal pulse has already been assigned to the second category, a point cloud is generated by means of the computer unit using entries corresponding to the second pulse width.

[0033] In such an embodiment, the second pulse width also corresponds to one of the parameters of the signal pulse.

[0034] If the radial distance is less than the limit distance, it can be assumed with high probability that the pulses generated by reflections from real objects provide a maximum amplitude greater than the second limit value. In other words, it can be assumed that signal pulses whose maximum amplitude does not reach the second limit value (and therefore the second pulse width is correspondingly equal to zero) are due to noise effects. Therefore, for such small radial distances, it is advantageous to use a second pulse width to generate point clouds. This reduces the influence of noise.

[0035] According to at least one embodiment, at least two categories comprise at least three categories, or more precisely, three categories. Specifically, at least two categories comprise a first category, a second category, and a third category. If the radial distance is less than a limit distance and the second pulse width is equal to zero, the signal pulse is assigned to the third category of the at least three categories, particularly by means of a computer unit. If the signal pulse has already been assigned to the third category, a point cloud is generated, particularly by means of a computer unit, using entries corresponding to the first pulse width.

[0036] In this case, only the first pulse width is relevant because the second pulse width is zero. Therefore, entries are generated using the first pulse width. If the radial distance is less than the limit distance and the second pulse width is zero, it can be assumed with high probability that the corresponding signal pulse is caused by signal noise or other noise effects.

[0037] This information can be stored in the point cloud, for example, by using identifiers, so that entries for the third category of signal pulses are no longer considered for specific subsequent applications.

[0038] According to at least one embodiment, the entry includes an identifier indicating the category to which the signal pulse is assigned.

[0039] Therefore, an identifier can be understood as a flag that can take as many different values ​​as the different categories of signal pulses.

[0040] In subsequent applications, such as object classification, the pulse widths involved in each entry can be determined by using identifiers, and the pulse widths can be used individually accordingly.

[0041] Storing identifiers requires very little memory. In the case of two categories, each entry requires only one bit, while in the case of three or four categories, each entry requires only two bits. This results in significant savings in storage space, especially compared to storing two complete entries, for example, if two different point clouds are already stored.

[0042] According to at least one embodiment, in particular by means of a computer unit, objects are automatically classified based on point clouds and simultaneously taking into account entries.

[0043] Specifically, classification is performed based on either the first or second pulse width, depending on which of the two pulse widths the entry corresponds to.

[0044] According to at least one embodiment, classification is performed based on the identifier of the entry.

[0045] For example, an identifier indicating that an entry in the third category may not be used for classification. As mentioned above, since entries in the third category indicate the influence of noise effects, the latter's influence on classification can be reduced, which can lead to a more reliable or accurate classification.

[0046] According to at least one embodiment, the second limit value is greater than the first limit value, and the first limit value is greater than the predetermined noise level of the detector unit.

[0047] This can advantageously prevent signal noise from being misinterpreted. Therefore, the reliability of the method is further increased.

[0048] According to at least one embodiment, the method includes determining a predetermined noise level based on test measurements.

[0049] Based on the improved concept, a method for at least partially automatic control of a motor vehicle is also provided. A point cloud for object recognition is generated using a method for object recognition based on the improved concept, and the motor vehicle is controlled at least partially automatically based on the point cloud, and particularly on the results of point cloud-based object classification, while considering entries.

[0050] According to at least one embodiment, the second limit value is greater than the first limit value, and the second limit value is greater than the predetermined saturation limit value of the detector element.

[0051] The saturation limit can, for example, correspond to the maximum detector current, such that the sensor signal is limited to the saturation limit, regardless of whether the intensity of the incident light may be higher.

[0052] Therefore, above the saturation limit, the pulse width is meaningless or equal to zero.

[0053] According to at least one embodiment, the saturation limit value is predetermined in the method by further test measurements.

[0054] According to at least one embodiment of a method for at least partially automatic control of a motor vehicle based on an improved concept, generating a point cloud for object recognition by means of a method for object recognition based on an improved concept involves automatically classifying the object based on the point cloud while considering entries. The motor vehicle is then controlled at least partially automatically based on the classification results.

[0055] Based on the improved concept, an active optical sensor system specifically for motor vehicles is also provided. The sensor system has a detector unit adapted to record light reflected by objects in the environment of the sensor system and generate a sensor signal based on the recorded light. The sensor system has a computer unit adapted to determine a first pulse width of a signal pulse of the sensor signal, the first pulse width being established by a predetermined first limit value of the amplitude of the sensor signal. The computer unit is adapted to determine a second pulse width of the signal pulse, the second pulse width being established by a predetermined second limit value of the amplitude of the sensor signal. The computer unit is adapted to assign the signal pulse to one of at least two categories according to at least one predefined parameter of the signal pulse and generate a point cloud for object recognition. The point cloud precisely contains an entry of the signal pulse, which corresponds either to the first pulse width or the second pulse width depending on the category of the signal pulse.

[0056] Specifically, the active optical sensor system has an emitter unit adapted to emit light in the direction of the object, and a detector unit adapted to record the component of the emitted light reflected by the object and generate a sensor signal based thereon.

[0057] Other embodiments of the active optical sensor system according to the improved concept are directly derived from various configurations of the method for object recognition according to the improved concept, and vice versa. In particular, the active optical sensor system according to the improved concept can be adapted or programmed to perform the method according to the improved concept, or to perform such a method.

[0058] According to the improved concept, an electronic vehicle guidance system for motor vehicles is also provided. The vehicle guidance system has an active optical sensor system according to the improved concept, and the vehicle guidance system has a control device adapted to generate at least one control signal based on a point cloud to at least partially automatically control the motor vehicle.

[0059] In this case, the control device may include a computer unit, for example, an active optical sensor system.

[0060] According to the improved concept, a motor vehicle is also provided, which has an electronic vehicle guidance system or an active optical sensor system according to the improved concept.

[0061] According to the improved concept, a first computer program having first instructions is provided. When the first instructions or the first computer program are executed by an active optical sensor system according to the improved concept, the first instructions cause the sensor system to execute a method for object recognition according to the improved concept.

[0062] According to the improved concept, a second computer program having second instructions is also provided. When the second instructions are executed by the electronic vehicle guidance system according to the improved concept, or when the second computer program is executed by the vehicle guidance system, the second instructions cause the vehicle guidance system to perform the method for at least partial automatic control of a motor vehicle according to the improved concept.

[0063] According to the improved concept, a computer-readable storage medium is also provided, on which a first computer program according to the improved concept and / or a second computer program according to the improved concept are stored.

[0064] According to the improved concept, a computer program and a computer-readable storage medium can be regarded as a corresponding computer program product having corresponding first and / or second instructions. Attached Figure Description

[0065] Other features of the invention can be found in the claims, drawings, and description of the figures. Without departing from the scope of the invention, the features and combinations of features mentioned in the above description, as well as the features and combinations of features mentioned in the following description of the figures and / or shown individually in the figures, can be used not only in the specific combinations shown, but also in other combinations. Therefore, embodiments of the invention that are not explicitly shown and explained in the figures, but arise and arise from the explained embodiments through individual combinations of features, are also intended to be considered included and disclosed. Therefore, embodiments and combinations of features that do not have all the features of the initially stated independent claims are also intended to be considered disclosed. Furthermore, embodiments and combinations of features that exceed or differ from the combinations of features set forth in the following references to the claims are intended to be considered disclosed, particularly those disclosed by the embodiments described above.

[0066] In the attached image:

[0067] Figure 1 A schematic diagram of a motor vehicle having an exemplary embodiment of an electronic vehicle guidance system according to an improved concept is shown;

[0068] Figure 2 A schematic diagram of the sensor signal of a detector unit according to an exemplary embodiment of an active optical sensor system based on an improved concept is shown.

[0069] Figure 3 A schematic diagram of another sensor signal of a detector unit according to another exemplary embodiment of an active optical sensor system based on an improved concept is shown;

[0070] Figure 4 A schematic diagram of another sensor signal of a detector unit according to another exemplary embodiment of an active optical sensor system based on an improved concept is shown;

[0071] Figure 5A schematic representation of a camera image and point cloud generated by another exemplary embodiment of an active optical sensor system according to an improved concept is shown;

[0072] Figure 6 A schematic representation of the camera image and point cloud is shown; and

[0073] Figure 7 A schematic representation of the camera image and point cloud is shown. Detailed Implementation

[0074] Figure 1 An exemplary embodiment of a motor vehicle 1 having a vehicle guidance system 6 according to an improved concept is shown schematically.

[0075] According to the improved concept, the electronic vehicle guidance system 6 specifically features an active optical sensor system 2. Optionally, the vehicle guidance system 6 may also have a control device 7.

[0076] The active optical sensor system 2 has a transmitter unit 2a, which includes, for example, an infrared laser. The sensor system 2 also has a detector unit 2b, which includes, for example, one or more optical detectors, such as an APD.

[0077] The sensor system 2 also has a computer unit 2c. The functions of the computer unit 2c, as described below, can also be performed by the control device 7 in various configurations, and vice versa.

[0078] The transmitter unit 2a emits a laser pulse 3a into the environment of the motor vehicle 1, where the laser pulse 3a is partially reflected by an object 4 and at least partially reflected back as a reflected pulse 3b toward the sensor system 2, particularly the detector unit 2b. The detector unit 2b, particularly its optical detector, records the reflected component 3b and generates a time-dependent sensor signal based on it, which has an amplitude proportional to the radiant intensity or radiant power of the recorded light 3b. Figure 2 and Figure 3 Examples of various signal pulses are shown in the figure.

[0079] Computer unit 2c determines a first time interval during which sensor signals 5a, 5b, 5c, and 5d exceed a first limit value G1. This first time interval corresponds to a first pulse width D1 of the corresponding signal pulses. Similarly, computer unit 2c determines a second pulse width D2, which is greater than the first limit value G1, by comparing sensor signals 5a, 5b, 5c, and 5d with a corresponding second limit value G2.

[0080] The computer unit 2c or control device 7 can then determine the characteristics of the object 4, such as the reflectivity or extent of the object 4, based on the first pulse width D1 and the second pulse width D2.

[0081] Specifically, the computer unit 2c or the control device 7 can classify the object 4 according to its characteristics or pulse widths D1 and D2.

[0082] Based on the classification results or the characteristics of the object, the control device 7 then generates, for example, control signals to control the motor vehicle 1 at least partially automatically.

[0083] Figure 2 Two exemplary sensor signals 5a and 5b are shown. When the signal pulse of sensor signal 5a reaches the saturation limit GS, its amplitude therefore exceeds the second limit G2, but this does not apply to the signal pulse of sensor signal 5b. However, both sensor signals exceed the first limit G1. Therefore, for both sensor signals 5a and 5b, the first pulse width D1 is greater than zero. On the other hand, the second pulse width D2 is greater than zero only for sensor signal 5a, and equal to zero for sensor signal 5b.

[0084] For example, if the APD is used as an optical detector, the saturation limit GS can be on the order of several hundred mV, for example, between 100 mV and 1000 mV.

[0085] Figure 3 Another example of two additional sensor signals 5c and 5d is shown. Here, for both sensor signals 5c and 5d, the first pulse width D1 and the second pulse width D2 are both greater than zero.

[0086] Computer unit 2c generates point clouds based on signal pulses, specifically based on a first pulse width D1 or a second pulse width D2, respectively. For this purpose, the signal pulses are assigned to one of three categories I, II, and III, such as… Figure 4 The image is a schematic representation.

[0087] If the radial distance r determined for the signal pulse based on time-of-flight measurements is greater than a predetermined limit distance R, then the object 4 near the vehicle 1 is unlikely to reflect light with a sufficiently high intensity exceeding the second limit value G2, and therefore the second pulse width D2 is greater than zero. Accordingly, the signal pulse is assigned to the first category I in this case. For signal pulses of category I, the corresponding entries of the signal pulse are generated in a manner that makes it reproduce the first pulse width D1.

[0088] However, if the radial distance r is less than the limit distance R, then the pulse that does not reach the second limit value G2 can be considered unreliable due to noise effects or other reasons.

[0089] Therefore, signal pulses with a specific radial distance less than the limit distance R and a second pulse width D2 greater than zero are assigned to the second category II, while signal pulses with a radial distance r less than the limit distance R and a second pulse width D2 equal to zero are assigned to the third category III.

[0090] For signal pulses of category II, the entry for the point cloud relates to the second pulse width D2, while for signal pulses of category III, the entry relates to the first pulse width D1.

[0091] Figure 5 Point cloud 9 is schematically shown, generated based on the described improved concept. Only those points corresponding to category I or category II are represented in point cloud 9. The signal pulse for category III is not shown. This can be achieved by assigning an identifier or flag to each entry, indicating the corresponding category I, II, or III, or by storing such an identifier for each entry.

[0092] In this way, points in category III can be filtered out because they are very likely caused by noise.

[0093] However, by taking into account signal pulses with radial distance r greater than the limit distance R together with the second pulse width D2, even points at relatively large distances from the distance sensor system are represented in the point cloud 9.

[0094] Figure 5 The corresponding camera image 8 is also shown schematically.

[0095] Figure 6 This schematically represents another point cloud. Figure 6 In point clouds, the use of and for generating Figure 5 The point cloud 9 is based on the same signal pulses. However, for Figure 6 The second pulse width D2 is used for each entry. From Figure 5 and Figure 6 The comparison shows that Figure 6 The effective range in the point cloud is smaller than Figure 5 The effective range of point cloud 9.

[0096] Figure 7 Another point cloud is shown, which is also based on the same signal pulses. However, for Figure 7 The first pulse width D1 is used for all signal pulses. Accordingly, it can be seen that this range is related to... Figure 5 The point cloud 9 provides a fairly wide range. However, in the near field, Figure 7 The point cloud contains additional points, which are likely caused by noise.

[0097] As mentioned above, the improved concept makes it possible to provide point clouds for object recognition or classification, which has less noise impact and simulates the high sensitivity of sensor systems. Furthermore, the improved concept saves storage space, especially compared to storing two complete point clouds.

[0098] In various configurations of the improved concept, a hybrid point cloud is thus generated to convert analog signal pulses to the discrete domain. For example, each point can be assigned a flag based on its radial distance from the sensor system and the maximum amplitude of the signal pulse. Points with small radial distances and similarly small maximum amplitudes can then be filtered out, as they are likely due to interference or noise.

Claims

1. A method for object recognition using an active optical sensor system (2), wherein The detector unit (2b) of the sensor system (2) records the light (3b) reflected by the object (4) in the environment of the sensor system (2), and generates sensor signals (5a, 5b, 5c, 5d, 5e, 5f) based on the recorded light (3b); The computer unit (2c) determines the first pulse width (D1) of the signal pulses of the sensor signals (5a, 5b, 5c, 5d, 5e, 5f), and the first pulse width (D1) is established by a predetermined first limit value (G1) of the amplitude of the sensor signals (5a, 5b, 5c, 5d, 5e, 5f). Its features are, With the help of the computer unit (2c), The second pulse width (D2) of the signal pulse is determined, and the second pulse width (D2) is established by a predetermined second limit value (G2) of the amplitude of the sensor signals (5a, 5b, 5c, 5d, 5e, 5f); The signal pulse is assigned to one of at least two categories based on at least one predetermined parameter of the signal pulse; A point cloud (9) is generated for object recognition, the point cloud precisely containing an entry of the signal pulse, the entry corresponding to either the first pulse width (D1) or the second pulse width (D2) according to the category of the signal pulse. The radial distance between the object (4) and the sensor system (2) is determined by means of the computer unit (2c) based on the signal pulse; and Based on the radial distance, the signal pulse is assigned to one of at least two categories. Furthermore, the second limit value (G2) is greater than the first limit value (G1); If the radial distance is greater than a predetermined limit distance (R), then the signal pulse is assigned to the first category of the at least two categories; and If the signal pulse has been assigned to the first category, the point cloud (9) is generated using the entry corresponding to the first pulse width (D1).

2. The method as described in claim 1, characterized in that, If the radial distance is less than the limit distance (R) and the second pulse width (D2) is greater than zero, then the signal pulse is assigned to the second category of the at least two categories; as well as If the signal pulse has been assigned to the second category, the point cloud (9) is generated using the entry corresponding to the second pulse width (D2).

3. The method as described in claim 1 or 2, characterized in that, The at least two categories contain at least three categories; If the radial distance is less than the limit distance (R) and the second pulse width (D2) is equal to zero, then the signal pulse is assigned to the third category of the at least three categories; as well as If the signal pulse has been assigned to the third category, the point cloud (9) is generated using the entry corresponding to the first pulse width (D1).

4. The method as described in claim 1 or 2, characterized in that, The entry contains an identifier indicating the category to which the signal pulse has been assigned.

5. The method as described in claim 1 or 2, characterized in that, Based on the point cloud (9) and taking into account the entries, the objects (4) are automatically classified.

6. The method as described in claim 1 or 2, characterized in that, The second limit value (G2) is greater than the first limit value (G1), and the first limit value (G1) is greater than the predetermined noise level of the detector unit (2b); and / or The second limit value (G2) is greater than the first limit value (G1), and the second limit value (G2) is greater than the predetermined saturation limit value (GS) of the detector unit.

7. A method for at least partially automatic control of a motor vehicle (1), characterized in that, Point clouds (9) for object recognition are generated by means of the method described in any one of the preceding claims; and The motor vehicle (1) is controlled at least partially automatically based on the point cloud (9).

8. The method as described in claim 7, characterized in that, The point cloud (9) is generated by means of the method as described in claim 5; and The motor vehicle is controlled at least partially automatically based on the classification results (1).

9. An active optical sensor system (2), having The detector unit (2b) is adapted to record light (3b) reflected by an object (4) in the environment of the sensor system (2) and generate sensor signals (5a, 5b, 5c, 5d, 5e, 5f) based on the recorded light (3b); The computer unit (2c) is adapted to determine a first pulse width (D1) of the signal pulses of the sensor signals (5a, 5b, 5c, 5d, 5e, 5f), the first pulse width (D1) being established by a predetermined first limit value (G1) of the amplitude of the sensor signals (5a, 5b, 5c, 5d, 5e, 5f). Its features are, The computer unit (2c) is adapted to: The second pulse width (D2) of the signal pulse is determined, and the second pulse width (D2) is established by a predetermined second limit value (G2) of the amplitude of the sensor signals (5a, 5b, 5c, 5d, 5e, 5f); The signal pulse is assigned to one of at least two categories based on at least one predetermined parameter of the signal pulse; A point cloud (9) is generated for object recognition, the point cloud precisely containing an entry of the signal pulse, the entry corresponding to either the first pulse width (D1) or the second pulse width (D2) according to the category of the signal pulse. The radial distance between the object (4) and the sensor system (2) is determined by means of the computer unit (2c) based on the signal pulse; and Based on the radial distance, the signal pulse is assigned to one of at least two categories. Furthermore, the second limit value (G2) is greater than the first limit value (G1); If the radial distance is greater than a predetermined limit distance (R), then the signal pulse is assigned to the first category of the at least two categories; and If the signal pulse has been assigned to the first category, the point cloud (9) is generated using the entry corresponding to the first pulse width (D1).

10. An electronic vehicle guidance system for a motor vehicle (1), characterized in that, The vehicle guidance system (6) has the active optical sensor system (2) as described in claim 9; and The vehicle guidance system (6) has a control device (7) adapted to generate at least one control signal based on the point cloud (9) to control the motor vehicle (1) at least partially automatically.

11. A computer program product having instructions which, when executed by an active optical sensor system (2) as claimed in claim 9, cause the sensor system (2) to perform the method as claimed in any one of claims 1 to 6.

12. A computer program product having instructions that, when executed by an electronic vehicle guidance system (6) as claimed in claim 10, cause the vehicle guidance system (6) to perform the method as claimed in any one of claims 7 and 8.

13. A computer-readable storage medium storing a computer program product as described in any one of claims 11 and 12.

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