METHOD FOR DETERMINING OBJECT INFORMATION ABOUT AN OBJECT IN A VEHICLE ENVIRONMENT, CONTROL UNIT AND VEHICLE

DE502021010369D1Active Publication Date: 2026-05-13ZF CV SYST GLOBAL GMBH
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Patent Information

Authority / Receiving Office
DE · DE
Patent Type
Patents
Current Assignee / Owner
ZF CV SYST GLOBAL GMBH
Filing Date
2021-03-09
Publication Date
2026-05-13

AI Technical Summary

Technical Problem

Existing systems fail to detect objects, especially people lying on the ground, and determine spatial mapping of a vehicle's surroundings when stationary or moving at very low speeds, which is necessary for safety requirements in driverless industrial vehicles.

Method used

A method using a single camera with an active actuator system to adjust the camera's position without altering the vehicle's driving state, combined with triangulation to determine object information, and optionally using multiple cameras for enhanced reliability.

Benefits of technology

Enables spatial mapping and object detection, including classification, even when the vehicle is stationary or moving slowly, by accurately determining depth and object coordinates through controlled camera adjustments.

✦ Generated by Eureka AI based on patent content.
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Description

[0001] Method for determining object information about an object in a vehicle environment, control unit and vehicle.

[0002] The invention relates to a method for determining object information of an object in the environment of a vehicle, as well as a control unit and a vehicle for carrying out the method.

[0003] It is known from the prior art how, using a single camera, the structure of a scene can be determined in 3D by photogrammetric methods through the forward or backward movement of a vehicle on which the camera is mounted (so-called Structure from Motion (SfM)). Furthermore, it is known from the prior art that the determination of the baseline between two camera positions, which is either known or estimated for triangulation to determine depth, can be supported by evaluating odometry data from the vehicle.

[0004] US2018 / 0204072A1 further specifies the installation of cameras on a trailer of a vehicle combination. It also includes vehicle dynamics sensors that output odometry data relating to vehicle movement, such as vehicle speed. The camera data output is compared with the odometry data, which is used to compensate for vehicle movement when processing the camera data to create images. Camera data from different cameras can also be combined in this process.

[0005] DE 10 2005 009 814 B4 describes the processing of camera data together with odometry data output by wheel speed sensors to determine the yaw rate. DE 60 009 000 T2 further describes image processing, taking into account the vehicle's odometry data, to assist the driver with parking. DE 10 2015 105 248 A1 describes the processing of an image from a first camera together with an image from a second camera in conjunction with odometry data, whereby the cameras can be arranged on a trailer and a towing vehicle of a multi-section vehicle. The images captured by the various cameras and output as camera data are combined. This creates a combined image of the surroundings, taking into account, for example, the angle of rotation when cornering, which characterizes the relative positions of the cameras.A bird's-eye view can be overlaid on the entire multi-part vehicle to show the surroundings, for example to enable parking assistance.

[0006] WO 2016 / 164118 specifies an omnidirectional camera that captures object points in the vehicle's environment and outputs corresponding camera data. A control unit in the vehicle processes the camera data, incorporating odometry data. This odometry data, for example, from wheel speed sensors, position sensors, or a steering angle sensor, is received via the vehicle's data bus. The camera detects the object points of interest in the vehicle's environment, and the control unit uses the odometry data to determine the distance to the object associated with each captured object point. This is achieved by capturing multiple images from different viewpoints with overlapping fields of view.By tracking object points, depth information of the scene can be estimated using triangulation and bundle adjustment. The camera data is also displayed as images on a screen for the driver. These images, along with the determined distance, facilitate maneuvering a car as a towing vehicle to hitch up a trailer.

[0007] Other objects such as the ground, pedestrians, etc. can be detected, but this requires sufficient movement of the vehicle, as this is the only way to adjust different viewpoints for the camera.

[0008] From US2017116758A1, a device for distance measurement with a camera, which is movably arranged on a camera carrier, is known, together with a control unit configured to control the movement of the camera, particularly in the stationary state of the device, such that the camera captures at least two images in at least two positions. This device includes a computing unit configured to calculate and output the distance of the device to objects visible in the images, based on the at least two images.

[0009] From US2019056749A1, a driver assistance system is known that comprises a camera and at least one processor. The camera is mounted on a bracket that is rotatably coupled to a vehicle and rotates about an axis of rotation spaced apart from the camera. The camera is configured to rotate together with the mounting bracket from a first point to a second point and to capture an external image of the vehicle at both the first and second points. The processor is configured to control the camera to capture a first image at the first point and a second image at the second point, to detect an object around the vehicle based on the first and second images, and to determine the distance between the object and the vehicle.

[0010] A disadvantage of this technology is that, for example, detecting people lying on the ground when the vehicle is stationary or moving at very low, unresolvable speeds is not possible. Similarly, other objects in the vehicle's vicinity cannot be detected using "Structure from Motion" if the vehicle is stationary or moving very slowly. Therefore, when stationary, a single camera cannot achieve spatial mapping of the vehicle's surroundings or an object, meaning that neither automated object classification nor distance determination is possible.

[0011] However, the safety requirements for driverless industrial vehicles, such as those specified in ISO 3691-4, necessitate the detection of people lying on the ground. This means that they must be identified before departure, i.e., when stationary or at very low speeds. Furthermore, distance measurements, object classifications, or the determination of other spatial object information cannot be performed with existing systems at traffic lights or in parking situations.

[0012] The object of the invention is therefore to provide a method for determining object information of an object, which enables a spatial view of the vehicle's surroundings using only one camera, even when the vehicle is stationary or at very low speeds. A further object is to provide a control unit and a vehicle.

[0013] This task is solved by a method, a control unit, and a vehicle according to the independent claims. The dependent claims specify preferred embodiments.

[0014] Accordingly, a generic method for determining object information about an object in the vicinity of a vehicle is provided, wherein the vehicle has at least one camera, with at least the following steps: Capturing the environment with at least one camera from a first position and, depending on this, creating a first image consisting of first pixels; changing the position of the at least one camera; capturing the environment with at least one camera from a second position and, depending on this, creating a second image consisting of second pixels, whereby the first position differs from the second position due to an intermediate change in the camera's position;Determining object information for an object in the captured environment by: selecting at least one first pixel in the first image and at least one second pixel in the second image, wherein the first pixel and the second pixel are selected such that they are assigned to the same object point of the object in the captured environment, and determining object coordinates of the assigned object point from the first image coordinates of the at least one first pixel and the second image coordinates of the at least one second pixel by triangulation, assuming a base length between the two camera positions.

[0015] According to the invention, the change in the viewpoint of the at least one camera from the first viewpoint to the second viewpoint is effected by controlling an active actuator system in the vehicle. The active actuator system adjusts the at least one camera by a certain amount of travel without altering the vehicle's driving state. Driving state is understood to mean the vehicle's overall state of motion, i.e., for example, stationary or traveling at a specific speed. The active actuator system does not change this motion; the adjustment range is therefore not linked to the vehicle's movement. Thus, the active actuator system differs from a drive system or a braking system, which directly affect the overall state of motion of the vehicle.

[0016] Advantageously, the method according to the invention achieves the ability to determine depth information or object information with just one camera, independent of the vehicle's driving state. This allows the depth information, or, to an approximate extent, the 3D position or object coordinates of the respective object point, to be determined by triangulation even when the vehicle is stationary or when its speed is so low that odometry data cannot reliably provide information about the movement between the two viewpoints. This requires only controlled actuation of the active actuator system, which is independent of the vehicle's movement. Through triangulation, at least rudimentary depth information, such as an object shape or contour, can be obtained, even without precise knowledge of a certain baseline length.

[0017] This means that the actuator system for adjusting the camera between positions is not limited to stationary or low-speed vehicle operation. Additional adjustments can also be made while driving using the active actuator system. This allows for more flexible object information acquisition under different driving conditions and situations.

[0018] Preferably, the baseline length between the two viewpoints is determined from the vehicle's odometry data. This odometry data is generated at least as a function of the camera's movement and characterizes its adjustment between the two viewpoints. Thus, the baseline length is no longer simply assumed but determined as a function of the actively controlled movement, resulting in more accurate triangulation. The movement can be used in addition to the vehicle's movement (if available) to determine depth information or object coordinates, provided it is considered alongside the standard odometry data relating to the vehicle's driving state. This allows for more precise and flexible determination of object and depth information, even under varying driving conditions.

[0019] Preferably, the active actuator system is a camera adjustment system comprising actuators and / or pneumatic cylinders and / or hydraulic cylinders and / or electric servo cylinders, wherein the at least one camera is directly attached to the camera adjustment system, so that when the camera adjustment system is actuated, the at least one camera is moved by the adjustment path to change its position. Thus, according to one embodiment, the camera can be adjusted directly without moving the vehicle or its components, with the camera adjustment system being mounted and aligned accordingly on the vehicle.

[0020] Preferably, it is further provided that an active air suspension system with air springs (ECAS) or a chassis adjustment system is used as the active actuator system, wherein by controlling the active air suspension system or the chassis adjustment system a vehicle body is adjusted in height by the adjustment path, so that the at least one camera attached to the vehicle body is indirectly adjusted by the adjustment path to change the position of the at least one camera.

[0021] This allows for the advantageous use of an actuator system already present in the vehicle, enabling it to perform a dual function. For example, it can raise and lower the vehicle body for air suspension, stabilize (rolling, pitching), etc., and simultaneously adjust the camera to different viewpoints. The air suspension or chassis adjustment system simply needs to be activated in the relevant situation, which is possible in all driving situations, including when stationary. In this case, the camera can be freely mounted on the vehicle body to move with it.

[0022] Preferably, it is further provided that a component adjustment system is controlled as an active actuator system, wherein by controlling the component adjustment system a component of the vehicle, for example a driver's cab and / or an aerodynamic component, is adjusted by the adjustment path, so that the at least one camera attached to this component is indirectly adjusted by the adjustment path to change the position of the at least one camera.

[0023] This allows the use of an actuator system that doesn't raise, lower, or adjust the entire vehicle structure, but only individual parts or components. Such adjustment systems are already present in certain vehicles, so they don't need to be retrofitted. The camera then simply needs to be attached to this component.

[0024] The aforementioned active actuator systems can be provided individually or in combination with each other, for example to increase variability and to enable combined adjustments with possibly extended adjustment ranges.

[0025] Preferably, the vehicle is also provided that, when the active actuator system is activated, it is in a driving state where its speed is below a certain limit or where it is stationary. This makes the method advantageously suitable for situations where conventional odometry using available odometry data, such as wheel speed signals, articulation angles, steering angles, etc., cannot reliably determine the object's depth information because this data is too imprecise. The active adjustment of the camera according to the invention makes the method independent of the vehicle's movement.

[0026] Preferably, the object coordinates or object information for multiple object points are determined by triangulation from at least two images, and an object contour and / or shape is derived from these multiple object points. The object can then preferably be subdivided into object classes based on its contour and / or shape. This allows for the simple recognition and classification of objects, especially stationary objects such as people, even when the object is stationary.

[0027] According to a further development plan, multiple cameras are used, and each camera is independently adjusted by a specified distance to determine object information about an object based on the disparity or base length, as described. This allows depth information or object information to be obtained preferably from multiple sources, thereby increasing reliability. Furthermore, this also enables the plausibility check of the object information obtained by the multiple cameras.

[0028] Preferably, more than two images are captured from different viewpoints, and pixels are selected from each captured image that correspond to the same object point of the object in the captured environment. The object coordinates of the corresponding object point are then determined from the image coordinates of the selected pixels by triangulation, assuming a baseline length between the respective camera viewpoints. This allows the respective object or object point to be tracked over a longer period of time in order to determine the depth information or the respective object information more accurately and robustly, possibly by means of beam alignment. Furthermore, several pixels can be grouped into one or more feature points, and the temporal correspondence of this feature point(s) between the respective images can be determined by triangulation.

[0029] Additionally, the system can provide for the plausibility check of object information derived from camera adjustments via the active actuator system, or from the adjustment path itself as odometry data. This plausibility check can be performed using object information derived from the vehicle's odometry data, selected from the following groups: wheel speed signal, vehicle speed, steering angle, and / or articulation angle. This allows for the comparison of object information obtained from different camera movements. For example, if the vehicle speed is very low, the reliability of depth information derived from wheel speeds cannot be guaranteed, such as with passive wheel speed sensors. Therefore, to further validate the object information, the camera can be adjusted via the active actuator system to obtain the depth information.

[0030] According to the invention, a control unit and a vehicle with such a control unit for carrying out the described methods are further provided, wherein the vehicle is one-piece or multi-piece and the at least one camera is arranged on a towing vehicle (with or without trailer) and / or on a trailer of the vehicle.

[0031] The invention is explained in more detail below using an exemplary embodiment. The figures show: Fig. 1 a driving situation of a multi-part vehicle; Fig. 1a a detailed view of the multi-part vehicle; Fig. 2a an image taken by the camera; Fig. 2b the recording of an object point with a camera from different viewpoints; and Fig. 3 a flowchart of the method according to the invention.

[0032] In Figur 1 The diagram schematically depicts a multi-part vehicle 1 consisting of a towing vehicle 2 and a trailer 3, wherein, according to the illustrated embodiment, a camera 4 with a detection range E is arranged on each of the vehicle parts 2 and 3. A towing vehicle camera 42 with a towing vehicle detection range E2 is arranged on the towing vehicle 2, and a trailer camera 43 with a trailer detection range E3 is arranged on the trailer 3. The cameras 4, 42, and 43 each output camera data KD, KD2, and KD3, respectively.

[0033] Vehicle 1 can be made up of multiple parts, as shown in Fig. 1 depicted, for example, as a truck and trailer combination with a drawbar trailer or turntable trailer, or as a semi-trailer truck with a tractor unit and semi-trailer. However, vehicle 1 can also be a single unit, as shown in Fig. 1a The orientation of camera 4 is shown. The orientation of camera 4 is chosen depending on the specific application.

[0034] The respective camera data KD, KD2, KD3 are generated depending on an environment U around the vehicle 1, towards which the respective detection area E, E2, E3 is directed. From the camera data KD, KD2, KD3, an image B consisting of pixels BPi with image coordinates xB, yB can be generated (see figure). Fig. 2a ) create, where each pixel BPi is assigned an object point PPi in the environment U (see Fig. 2b The object points PPi belong to objects O located in the environment U, to which specific absolute object coordinates xO, yO, zO can be assigned in space. Depending on the position SP of the respective camera 4, 42, 43, object points PPi of an object O are mapped onto different image points BPi or with different image coordinates xB, yB in the images B.

[0035] The camera data KD, KD2, KD3 from the respective cameras 4, 42, 43 are transmitted to a control unit 5, which is configured to determine object information OI by means of a triangulation T, based on the camera data KD, KD2, KD3 and on selected odometry data DD of the vehicle 1, which relate to the current driving situation of the vehicle 1 or the sub-vehicles 2, 3 and thus also characterize the movement of the camera 4. The object information OI specifies, in particular, spatial characteristics of the respective object O detected by the cameras 4, 42, 43 in the environment U.

[0036] Object information (OI) includes, for example, the absolute object coordinates xO, yO, zO (world coordinates) of object O in space, and / or a distance A between a reference point PB, for example a rear side 1a of vehicle 1 (in the case of a single-part vehicle 1) or of trailer 3 (in the case of a multi-part vehicle 1) or a current position SP of the respective camera 4, 42, 43, and the detected object O or an object point PPi on object O or a related quantity, and / or an object shape OF or an object contour OC, which is subdivided, for example, into n different object classes OKn, and / or an object dynamic OD, i.e. a temporal movement of the detected object O in space, are in question.

[0037] The object information (OI) is determined according to the Structure-From-Motion (SfM) method, in which ST1, ST2, ST3 (see below) are calculated in sub-steps. Fig. 3 ) an object O is recorded by a camera 4 from at least two different viewpoints SP1, SP2 (see Fig. 2b Through triangulation T, depth information regarding the object O, or the respective object information OI, can be obtained in a further step ST4. How to Fig. 2b As described, image coordinates xB, yB are determined for at least one first image point BP1i in the first image B1 and for at least one second image point BP2i in the second image B2, which are each assigned to the same object point PPi (ST4.1).

[0038] To simplify the process, a certain number of pixels BP1i, BP2i in the respective image B1, B2 can be combined into a feature point MP1, MP2 (see Fig. 2a ), wherein the image points to be summarized BP1i, BP2i are chosen such that the respective feature point MP1, MP2 is assigned to a specific uniquely localizable feature M on the object O (see Fig. 2b ). The feature M can, for example, be a corner ME or an edge MK on the object O, which can be extracted from the entire images B1, B2 and whose pixels BP1i, BP2i can be summarized in the feature points MP1, MP2.

[0039] As an approximation, the object shape OF or object contour OC can be at least estimated by triangulation T from the image coordinates xB, yB of the individual image points BP1i, BP2i or the feature points MP1, MP2, which are assigned to the same object points PPi or feature M in the at least two images B1, B2. For this purpose, the image coordinates xB, yB of several image points BP1i, BP2i or several feature points MP1, MP2 can be subjected to triangulation T to obtain object coordinates xO, yO, zO, which, however, do not necessarily lie on the object O in space.

[0040] Without knowing the exact base length L, i.e., the distance between the different viewpoints SP1 and SP2 of camera 4, triangulation T yields object coordinates xO, yO, zO in unscaled form. Therefore, only an unscaled object shape OF or object contour OC can be derived from such determined object coordinates xO, yO, zO, which is sufficient for determining the shape or contour. For triangulation T, an arbitrary base length L can initially be assumed.

[0041] To enable the determination of further object information (OI) through triangulation T, the actual base length L is additionally used. If according to Fig. 2b If the relative positions, and thus the base length L, between the different viewpoints SP1 and SP2 of camera 4, from which the two images B1 and B2 were taken, are known or have been determined, then the absolute object coordinates xO, yO, zO (world coordinates) of object O, object point PPi, or feature M can also be determined by triangulation T. From this, the distance A between the reference point PB and the detected object O, or an object point PPi on object O, can be determined, whereby the coordinates of the reference point PB in the world coordinates follow directly from geometric considerations.

[0042] In this way, the control unit 5 can estimate a scaled object contour OC or scaled object shape PF compared to the case above if the exact object coordinates xO, yO, zO of several object points PPi or features M are determined. From the object contour OC, the object O can then be classified into a specific object class OKn. The object dynamics OD can also be taken into account, for example, a direction of movement R of the object point(s) PPi and / or an object velocity vO, if the object points PPi are considered with temporal resolution.

[0043] For example, objects identified as people can be classified in a first object class, OK1. Objects identified as stationary, such as signs, loading ramps, houses, etc., can be classified in a second object class, OK2. Objects identified as moving, such as other vehicles, can be classified in a third object class, OK3.

[0044] To determine the object information OI even more accurately, it may be additionally provided that more than two images B1, B2 are taken and evaluated by triangulation T as described above, and / or that a bundle adjustment BA is additionally carried out.

[0045] As already described, for the SfM method, object O must be viewed from at least two different viewpoints SP1 and SP2 from camera 4, as schematically shown in Fig. 2b As shown, in substep ST2, camera 4 is moved in a controlled manner to the different viewpoints SP1 and SP2. In the scaled case, the resulting base length L between viewpoints SP1 and SP2 is determined using odometry data DD (ST4, ST4.2). Various methods can be used for this: If the entire vehicle 1 is in motion, this already results in a movement of camera 4. This means that the vehicle 1 as a whole is set in motion actively, for example by a drive system 7, or passively, for example by a gradient. If at least two images B1 and B2 are recorded by camera 4 within a time offset dt during this movement, the base length L can be determined using odometry data DD, from which the vehicle movement and thus also the camera movement can be derived.Odometry is used to determine the two viewpoints SP1 and SP2 assigned to images B1 and B2.

[0046] Odometry data DD can be, for example, wheel speed signals SR from active and / or passive wheel speed sensors 6a, 6p on the wheels of the vehicle 1 (see. Fig. 1 ) can be used. From these, depending on the time offset dt, it can be determined how far the vehicle 1 or the camera 4 has moved between the viewpoints SP1, SP2, from which the base length L can be derived. However, it is not necessary to rely solely on vehicle odometry, i.e., the evaluation of vehicle movement based on motion sensors on vehicle 1. Visual odometry can also be used as a supplement or alternative. With visual odometry, a camera position can be continuously determined from the camera data KD of camera 4 or from information in the captured images B, B1, B2, provided that at least initially, object coordinates xO, yO, zO of a specific object point PPi are known. The odometry data DD can therefore also contain a dependency on the camera position determined in this way, since the vehicle movement between the two viewpoints SP1, SP2, or SP2 can be derived from it.The base length L can also be derived directly.

[0047] To improve the accuracy of the odometric determination of the base length L during movement of vehicle 1, additional odometry data DD available in vehicle 1 can be used. For example, a steering angle LW and / or a yaw rate G can be used to also account for the rotational movement of vehicle 1. In the case of a two- or multi-section vehicle 1, an articulation angle KW between the towing vehicle 2 and the trailer 3 can additionally be used to account for the exact dynamics of the trailer 3, especially during shunting operations.

[0048] If the single-part vehicle 1 or the multi-part vehicle 1 with its vehicle parts 2, 3 is not in motion, or if the motion within the time offset dt is so small that the odometry data DD is so inaccurate that a reliable determination of the base length L is not possible, the camera 4 can also be set in motion by an active actuator system 8 in sub-step ST2. The motion of the camera 4 caused by the actuator system 8 differs from the motion of the vehicle 1 considered so far, in particular in that the actuator system 8 only sets the camera 4 or a vehicle section connected to the camera 4 in motion. The motion of the vehicle 1 as a whole, or a driving state Z of the vehicle 1, is therefore not changed, so that a stationary vehicle 1 remains stationary SS when the actuator system 8 is actively controlled.

[0049] The actuator system 8 is controlled by the control unit 5 via actuator signals SA. This can occur, for example, if the control unit 5 detects that the odometry data DD, which characterizes the movement of the entire vehicle 1 (i.e., the wheel speed signals SR and / or the steering angle LW and / or the yaw rate G and / or the camera data KD), is not accurate or detailed enough to determine the base length L. This can happen if the vehicle 1 is stationary SS or if the vehicle speed v1 is lower than a speed limit vt.

[0050] When the actuator system 8 is activated, the camera 4 is moved directly or indirectly to different positions SP1 and SP2, so that the environment U can be captured in at least two different images B1 and B2. This allows the SfM method to be performed as described above. To determine the base length L, the control unit 5 uses a displacement W by which the camera 4 is moved between the two positions SP1 and SP2 by the actuator system 8. The displacement W is transmitted from the actuator system 8 to the control unit 5. The control unit 5 can therefore additionally incorporate the displacement W of the actuator system 8 into the odometry data DD to determine the base length L.

[0051] Various systems within the vehicle 1 are considered as actuator systems 8, which are located in Fig. 1aThe schematic diagrams shown here are examples for a single-unit vehicle 1, but they can also be used on sub-vehicles 2, 3 of multi-unit vehicles 1. For example, the camera 4 can be arranged on a camera adjustment system 9 with one or more actuators 9a, pneumatic cylinders 9b, hydraulic cylinders 9c, electric servo cylinders 9d, or similarly acting actuators, wherein the camera adjustment system 9 is attached to the vehicle 1 such that the detection area E is aligned as desired. In this case, the camera 4 can be moved to the different positions SP1, SP2 by adjusting the actuator(s) 9a, pneumatic cylinder 9b, hydraulic cylinder 9c, or servo cylinder(s) 9d by a specific travel W when actuated.

[0052] Another possibility for an active actuator system 8 is an active air suspension system 10 (ECAS, Electronically Controlled Air Suspension), which, in a single-unit vehicle 1 or, in the case of a multi-unit vehicle 1, in a towing vehicle 2 or also in a trailer 3, uses air springs 10a designed as spring bellows to ensure that a vehicle body 11 can be adjusted at a height H relative to the vehicle axles 1b, 2b, 3b of the vehicle 1 or the towing vehicle 2 or the trailer 3, i.e., raised or lowered. For this purpose, the pressure in the air springs 10a can be specifically adjusted.This can be used to achieve optimal suspension regardless of road conditions or load conditions, to dynamically compensate for changes in axle load distribution, to avoid swaying or pitching during cornering, or to adjust the height H of the vehicle body 11 during coupling of a towing vehicle 2 to a trailer 3 as well as during loading and unloading operations, for example at a loading ramp.

[0053] If the respective camera 4, 4a, 4b is arranged on the vehicle body 11 of the vehicle 1, the towing vehicle 2, or the trailer 3, the camera 4 can be adjusted, preferably in height H, by a travel W by the control unit 5, in order to position it at two different positions SP1, SP2. Since the travel W is known to the active air suspension system 10 and / or can be measured, it can also be transmitted to the control unit 5 so that the control unit can take the travel W effected by the active air suspension system 10 into account in the odometry data DD in order to determine the base length L.

[0054] In this way, the control unit 5, when the vehicle 1 is stationary (SS), can instruct the respective camera 4 to adjust via the active air suspension system 10, so that the respective object information (OI) for at least one object point (PPi) can also be determined via triangulation T using an SfM method. The control unit 5 can also specify the adjustment path (W) as a target value, which the active air suspension system 10 is to set by changing the pressure in the air springs 10a. However, to determine the object shape (OF) or the object contour (OC) unscaled via triangulation T, the adjustment path (W) (or the base length (L)) can also be disregarded, for example, if the adjustment path (W) is not measured or cannot be measured.

[0055] In addition to an active air suspension system 10, any comparable active suspension adjustment system 12 can also be used as a further active actuator system 8. This system is capable of adjusting the height H of the vehicle body 11 and thus positioning the camera 4 mounted on it at two different positions SP1 and SP2. A component adjustment system 13 is also possible as an active actuator system 8. This system can raise or lower only a part or component of the vehicle body 11, to which the camera 4 is attached, for example, a driver's cab 14, by the adjustment range W. Other possible components include aerodynamic components 15, such as aerodynamic wings or spoilers, on which a camera 4 can be mounted and which can be actively adjusted to precisely move the camera 4 by an adjustment range W.

[0056] This provides a number of possibilities to actively and specifically position the camera 4 at different viewpoints SP1, SP2 in order to take two pictures B1, B2 of an object O and to determine the respective object information OI (scaled or unscaled) for one or more object points PPi. Reference symbol list (part of the description)

[0057] 1 Vehicle 1a Rear of vehicle 1 1b Vehicle axle 1 2 Tractor unit 2b Vehicle axle of towing vehicle 2 3 Trailer 3b Vehicle axle of trailer 3 4 Camera 42 Tractor unit camera 43 Trailer camera 5 Control unit 6a Active wheel speed sensor 6p Passive wheel speed sensor 7 Drive system 8 Active actuator system 9 Camera adjustment system 9a Actuator 9b Pneumatic cylinder 9c Hydraulic cylinder 9d Electric servo cylinder 10 Active air suspension system (ECAS) 10a Air springs 11 Vehicle body 12 Chassis adjustment system 13 Component adjustment system 14 Cab 15 Aerodynamic component A Distance B Image B1 First image B2 Second image B A Bundle compensation B P Image points BP1 First image point BP2 II Second image point D D Odometry data D T Time offset E Camera detection range E2 First detection range of the towing vehicle camera E3 Second detection range of the trailer camera GG Rate of rotation H Height of the vehicle body KD Camera data of the camera KD2 First camera data of the towing vehicle camera KD3 Second camera dataof the trailer camera L Base length L Fiber optic angle M Feature MP1, MP2 Feature point M Corner (as feature) M Edge (as feature) O Object OC Object contour OD Object dynamics OF Object shape O I Object information OK Notable object class P B Reference point P P P Object point R Direction of movement SA Actuator signal SP Camera position 4 SP1 First camera position SP2 Second camera position S Wheel speed signals SS Standstill T Triangulation U Environment around the vehicle 1 v1 Vehicle speed vO Object speed vt Speed ​​limit W Adjustment range Z Driving state

Claims

1. Method for ascertaining an object information item (OI) relating to an object (O) in an environment (U) of a vehicle (1), wherein the vehicle (1) has at least one camera (4), the method comprising at least the following steps: - capturing the environment (U) from a first viewpoint (SP1) using the at least one camera (4) and, on the basis thereof, creating a first image (B1) consisting of first image points (BP1i) (ST1); - changing the viewpoint (SP) of the at least one camera (4) (ST2); - capturing the environment (U) from a second viewpoint (SP2) using the at least one camera (4) and, on the basis thereof, creating a second image (B2) consisting of second image points (BP2i) (ST3); - ascertaining an object information item (OI) relating to an object (O) in the captured environment (U) (ST4) by - selecting at least one first image point (BP1i) in the first image (B1) and at least one second image point (BP2i) in the second image (B2), wherein the first image point (BP1i) and the second image point (BP2i) are selected in such a way that they are assigned to the same object point (PPi) of the object (O) in the captured environment (U) (ST4.1), characterized by the further step of - determining object coordinates (xO, yO, zO) of the assigned object point (Ppi) from first image coordinates (xB, yB) of the at least one first image point (BP1i) and second image coordinates (xB, yB) of the at least one second image point (BP2i) by triangulation (T) assuming a base length (L) between the two viewpoints (SP1, SP2) of the camera (4), wherein the viewpoint (SP) of the at least one camera (4) is changed (ST2) from the first viewpoint (SP1) to the second viewpoint (SP2) by controlling an active actuator system (8) in the vehicle (1), wherein the active actuator system (8) adjusts the at least one camera (4) by an adjustment distance (W) without changing a driving state (Z) of the vehicle (1), wherein as the active actuator system (8) either an active pneumatic suspension system (10) with pneumatic springs (10a) or a chassis adjustment system (12) is controlled, wherein by controlling the active pneumatic suspension system (10) or the chassis adjustment system (12) a vehicle body (11) is adjusted with respect to its height (H) by the adjustment distance (W), with the result that the at least one camera (4) attached to the vehicle body (11) is indirectly adjusted by the adjustment distance (W) in order to change the viewpoint (SP) of the at least one camera (4).

2. Method according to claim 1, characterized in that as the active actuator system (8) a camera adjustment system (9) is controlled, which adjustment system has servomotors (9a) and / or pneumatic cylinders (9b) and / or hydraulic cylinders (9c) and / or electric servo cylinders (9d), wherein the at least one camera (4) is directly attached to the camera adjustment system (9), with the result that when the camera adjustment system (9) is controlled, the at least one camera (4) is adjusted by the adjustment distance (W) in order to change the viewpoint (SP) of the at least one camera (4).

3. Method according to either of the preceding claims, characterized in that as the active actuator system (8) a component adjustment system (13) is controlled, wherein by controlling the component adjustment system (13) a component of the vehicle (1), for example a driver's cab (14) and / or an aerodynamics component (15), is adjusted by the adjustment distance (W), with the result that the at least one camera (4) attached to this component is indirectly adjusted by the adjustment distance (W) in order to change the viewpoint (SP) of the at least one camera (4).

4. Method according to any of the preceding claims, characterized in that when the active actuator system (8) is controlled, the vehicle (1) is in a driving state (Z) in which the vehicle (1) has a vehicle speed (v1) lower than a limit speed (vt), or the vehicle is in a stationary state (SS).

5. Method according to any of the preceding claims, characterized in that the object coordinates (xO, yO, zO) are ascertained from the at least two images (B1, B2) for a plurality of object points (PPi) by triangulation (T) and an object contour (OC) and / or an object shape (OF) is ascertained from the plurality of object points (PPi).

6. Method according to claim 5, characterized in that the object (O) is classified into object classes (OKi) on the basis of the object contour (OC) and / or the object shape (OF).

7. Method according to any of the preceding claims, characterized in that a plurality of cameras (4) are provided and object information items (OI) relating to an object (O) are ascertained independently of each other using each camera (4) by adjusting it by the adjustment distance (W).

8. Method according to any of the preceding claims, characterized in that more than two images (B) are recorded at differing viewpoints (SP) and image points (BPi) that are assigned to the same object point (PPi) of the object (O) in the captured environment (U) are selected from each recorded image (B), wherein object coordinates (xO, yO, zO) of the assigned object point (PPi) are ascertained from the image coordinates (xB, yB) of the selected image points (BPi) by triangulation (T) assuming a base length (L) between the respective viewpoints (SP) of the camera (4).

9. Method according to any of the preceding claims, characterized in that a bundle adjustment (BA) is performed on the basis of the at least two recorded images (B1, B2).

10. Method according to any of the preceding claims, characterized in that a plurality of first image points (BP1i) in the first image (B1) are combined into a first feature point (MP1) and a plurality of second image points (BP2i) in the second image (B2) are combined to form a second feature point (MP2), wherein the first feature point (MP1) and the second feature point (MP2) are selected in such a way that they are assigned to the same feature (M) of the object (O) in the captured environment (U), wherein object coordinates (xO, yO, zO) of the assigned feature (M) are ascertained from first image coordinates (xB, yB) of the first feature point (MP1) and second image coordinates (xB, yB) of the second feature point (MP2) by triangulation (T) assuming a base length (L) between the two viewpoints (SP1, SP2) of the camera (4).

11. Control unit (5) for performing a method according to any of the preceding claims.

12. Vehicle (1) comprising a control unit (5) according to claim 11, wherein the vehicle (1) has a camera (4) and the vehicle (1) is made of one or more parts and the at least one camera (4) is arranged on a towing vehicle (2) and / or a trailer (3) of the multi-part vehicle (1).