WO2021110303A1 - Procédé d'étalonnage d'un capteur de mesure de distance d'un véhicule - Google Patents

Procédé d'étalonnage d'un capteur de mesure de distance d'un véhicule Download PDF

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Publication number
WO2021110303A1
WO2021110303A1 PCT/EP2020/078589 EP2020078589W WO2021110303A1 WO 2021110303 A1 WO2021110303 A1 WO 2021110303A1 EP 2020078589 W EP2020078589 W EP 2020078589W WO 2021110303 A1 WO2021110303 A1 WO 2021110303A1
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sensor
vehicle
transformation parameter
transformation
determined
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PCT/EP2020/078589
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German (de)
English (en)
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Manuel Schäfer
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Daimler Ag
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/497—Means for monitoring or calibrating
    • G01S7/4972—Alignment of sensor
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/86—Combinations of sonar systems with lidar systems; Combinations of sonar systems with systems not using wave reflection
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/88—Sonar systems specially adapted for specific applications
    • G01S15/93—Sonar systems specially adapted for specific applications for anti-collision purposes
    • G01S15/931—Sonar systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/86—Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
    • G01S17/931—Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28—Details of pulse systems
    • G01S7/285—Receivers
    • G01S7/295—Means for transforming co-ordinates or for evaluating data, e.g. using computers
    • G01S7/2955—Means for determining the position of the radar coordinate system for evaluating the position data of the target in another coordinate system
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/40—Means for monitoring or calibrating
    • G01S7/4004—Means for monitoring or calibrating of parts of a radar system
    • G01S7/4026—Antenna boresight
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
    • G01S7/52004—Means for monitoring or calibrating
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
    • G01S7/523—Details of pulse systems
    • G01S7/526—Receivers
    • G01S7/53—Means for transforming coordinates or for evaluating data, e.g. using computers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/88—Sonar systems specially adapted for specific applications
    • G01S15/89—Sonar systems specially adapted for specific applications for mapping or imaging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G01S2013/9323—Alternative operation using light waves
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G01S2013/9324—Alternative operation using ultrasonic waves

Definitions

  • the invention relates to a method for calibrating a distance-measuring sensor of a vehicle.
  • the driver assistance system comprises a large number of sensors, to which calibration parameters are assigned, and storage means for the central storage of the calibration parameters.
  • the invention is based on the object of specifying a method for calibrating a distance-measuring sensor of a vehicle which is improved over the prior art.
  • the object is achieved according to the invention by a method for calibrating a distance-measuring sensor of a vehicle having the features of claim 1.
  • a transformation parameter value of at least one transformation parameter for a coordinate transformation is determined, with which a measurement position determined in a sensor coordinate system is transformed into a world coordinate system.
  • the transformation parameter value of the at least one transformation parameter is determined by an optimization method in which measurement positions that were determined with the sensor at different points in time during the vehicle's own movement are evaluated.
  • the optimization process includes the following steps: a) transformation of the measurement positions with a predetermined transformation parameter value of the at least one transformation parameter into a coordinate grid of the world coordinate system, b) counting cells of the coordinate grid to which at least one of the transformed measurement positions is assigned, c) repeating steps a) and b) with one in each case, ie with each repetition, modified transformation parameter value of the at least one transformation parameter and determining the transformation parameter value of the at least one transformation parameter, which leads to a minimum in step b), ie to a minimum of a number of the cells of the coordinate grid to which at least one of the transformed measurement positions is assigned.
  • the basic idea of the method is therefore to represent the surroundings of the vehicle detected by the sensor with as few cells as possible of the coordinate grid, which is formed from these cells, each with a finite extent.
  • point measurements of the sensor in the world coordinate system ie. H. into a world-fixed coordinate system, which is quantized in cells of a given size.
  • a respective object point of a respectively detected static object i.e. a respective world-fixed object point
  • a calibrated sensor With a decalibrated sensor, however, the same world-fixed object point will appear in measurements at different times during the vehicle's own movement at different positions in the world coordinate system, i.e.
  • different transformed measurement positions are determined for the same world-fixed object point of the static object at different points in the world coordinate system, which means that with the same world-fixed object point of the static object due to the resulting multiple transformed measurement positions, multiple cells of the coordinate grid are occupied.
  • the aim of the optimization process is therefore to determine the number of required, i.e. H. to minimize cells occupied by at least one transformed measurement position by adapting the transformation parameter value of the at least one transformation parameter, advantageously by adapting a respective transformation parameter value of a plurality of transformation parameters.
  • the number of these required, i.e. H. cells occupied with at least one transformed measuring position is minimal with optimal calibration of the sensor, since then the same transformed measuring position is recorded in the world coordinate system in all measurements for the respectively recorded world-fixed object point.
  • the number of transformed measurement positions is thus reduced to the number of acquired object points, as a result of which the number of transformed measurement positions and thus the number of cells occupied by the transformed measurement positions is minimal.
  • the method according to the invention works in particular with any surroundings of the vehicle. No preconditions need to be met in the scenarios to be recorded by means of the sensor for the method to work. Appropriately, only at least one stationary object needs to be detectable. However, this does not have to be a specific test object, but any stationary object is sufficient, for example a building, a curb, a guardrail, a delineator post or another structure, for example a piece of furniture in a building or an interior design of the building , for example a production hall in which the vehicle is manufactured.
  • the method according to the invention also works in scenarios with dynamic objects. These dynamic objects generate a different measurement position for each object point, since the object points in dynamic objects are not fixed in the world, at different times because the same object point is located at the different times due to the dynamic movement of the object different locations, and thus also different transformed measurement positions. Since the respective object point of such a dynamic object is therefore not located at the same location at different times, there will be no multiple transformed measurement positions for the same object point at the same location resulting from the decalibration of the sensor, which are reduced to one transformed measurement position by the calibration would. I. E.
  • the number of transformed measurement positions and thus also the number of cells occupied by these transformed measurement positions remains the same after calibration as before calibration; it therefore does not change during the optimization process and therefore has no influence on this optimization the minimization of the occupied cells.
  • This minimization of the occupied cells takes place exclusively through the reduction of the transformed measurement positions of the detected static objects.
  • the method according to the invention is also robust to distance noise from individual point measurements due to the quantization of the world coordinate system in cells.
  • a transformation parameter value is determined for at least one transformation parameter embodied as an extrinsic sensor parameter of the sensor and / or for a transformation parameter embodied as a time offset between a sensor-internal clock of the sensor and a clock of the vehicle's own movement module.
  • the at least one transformation parameter designed as an extrinsic sensor parameter is, for example, an x coordinate, a y coordinate or a z coordinate of an installation position of the sensor in a vehicle coordinate system or a roll angle, a pitch angle or a yaw angle of the sensor with respect to the vehicle coordinate system.
  • transformation parameter values of several transformation parameters are used for the Coordinate transformation determined with which a measuring position determined in the sensor coordinate system is transformed into the world coordinate system.
  • a transformation parameter value is determined for the respective transformation parameter.
  • the transformation parameter values of the transformation parameters are determined by the optimization method, in which measurement positions that were determined with the sensor at different points in time during the vehicle's own movement are evaluated.
  • the optimization method accordingly comprises the following steps: a) Transformation of the measuring positions with a predetermined transformation parameter value of the respective transformation parameter in the coordinate grid of the world coordinate system, b) Counting the cells of the coordinate grid to which at least one of the transformed measuring positions is assigned, c) Repeating steps a) and b) with in each case, ie with each repetition, modified transformation parameter values of the transformation parameters and determining the transformation parameter values of the transformation parameters, ie the transformation parameter value of the respective transformation parameter, which in step b) lead to a minimum, ie to a minimum of the number of cells in the coordinate grid, to which at least one of the transformed measurement positions is assigned.
  • the transformation parameter value of only one transformation parameter or the respective transformation parameter value of several or all transformation parameters is modified at the same time.
  • the method thus advantageously enables a temporal calibration, through the time synchronization between the sensor and the self-movement module, i.e. by determining the time offset between the sensor-internal clock of the sensor and the clock of the self-movement module of the vehicle, and at the same time a spatial calibration, advantageously in six degrees of freedom , ie with respect to the x-axis, y-axis and z-axis of the vehicle coordinate system and with respect to the roll angle, a pitch angle and yaw angle to the vehicle coordinate system.
  • a lidar sensor, a radar sensor, an ultrasound sensor or a stereo camera of the vehicle is calibrated as the sensor, ie in particular an environment detection sensor of the vehicle.
  • environment detection sensors are particularly advantageous for performing one or more assistance functions of the vehicle and / or by carrying out an at least partially automated or fully automated or autonomous ferry operation of the vehicle.
  • the respective sensor is calibrated in order to deliver exact sensor results and thereby avoid possible malfunctions of the assistance function or the at least partially automated or fully automated or autonomous ferry operation of the vehicle.
  • the vehicle's own movement is determined in particular by means of a vehicle's own movement module.
  • the data on the vehicle's own movement advantageously supplied by this self-movement module are required for the transformation from the sensor coordinate system into the world coordinate system, this transformation expediently taking place via a vehicle coordinate system as an intermediate step.
  • the transformation from the sensor coordinate system into the vehicle coordinate system takes place in particular by means of the extrinsic sensor parameters and the transformation from the vehicle coordinate system into the world coordinate system by means of the time synchronization between the sensor and the self-movement module, i. H. by means of the determined time offset between the internal clock of the sensor and the clock of the vehicle's own movement module.
  • the calibration by means of this method is carried out, for example, at one end of the production line for the vehicle.
  • This is also referred to as end-of-line calibration, which is possible by means of the method in a particularly quick and simple manner and without additional effort. Instead of laboriously measuring the vehicle, it is advantageously sufficient to drive the vehicle a few meters. This enables a process chain to be accelerated considerably.
  • the end-of-line calibration is one of the most time-consuming steps in vehicle construction.
  • the calibration is carried out by means of this method, for example during regular ferry operation of the vehicle.
  • the method can be used here, for example, to continuously carry out the calibration of the sensor while the vehicle is in motion and / or to detect whether the sensor is decalibrated, for example due to a mechanical defect.
  • the calibration is carried out by means of this method, for example during a data determination for the creation of at least one high-resolution digital map.
  • a highly accurate object detection and object position detection can take place by means of the sensor calibrated in this way, in order to thereby improve the accuracy of the high-resolution digital map.
  • the method can be applied to recorded sequences of the sensor detection in order to obtain a high-precision calibration.
  • This calibration by means of recorded sequences of the sensor detection can also be used, for example, to serve as a reference for an online calibration.
  • at least one calibration is carried out in which measurement positions that were determined with the sensor at different times within a short period of time during the vehicle's own movement are evaluated, and also, in particular, as Reference for this online calibration and thus to check it, at least one calibration is carried out in which measurement positions that were determined with the sensor at different times within a longer period of time during the vehicle's own movement are evaluated.
  • the longer period of time advantageously includes the points in time of the shorter period of time and additional points in time at which measurement positions were determined with the sensor. In this way, the online calibration can be carried out quickly and in quick succession. A longer period of time and thus also a longer computing time is then available for checking them in order to evaluate the correspondingly higher number of measurement positions.
  • a method for calibrating the distance-measuring sensor of the vehicle in particular with regard to the vehicle's own movement, is carried out, wherein calibration means that transformation parameters, in particular transformation parameter values of the transformation parameters, are determined for the coordinate transformation, with which a measuring position determined in the sensor coordinate system is converted into the World coordinate system is transformed.
  • transformation parameters in particular their transformation parameter values, are determined by an optimization method in which measurement positions that were determined with the sensor at different points in time, be evaluated.
  • the optimization method is advantageously based on the steps: a) transforming the measurement positions with predetermined transformation parameters, in particular predetermined transformation parameter values of the transformation parameters, into a coordinate grid of the world coordinate system, b) counting the cells of the coordinate grid to which at least one of the transformed measurement positions is assigned, c) repeating of steps a) and b) with modified transformation parameters, in particular modified transformation parameter values of the transformation parameters, and determining the transformation parameters, in particular their transformation parameter values, which lead to a minimum in step b).
  • FIG. 1 schematically shows several time-shifted measurements of a decalibrated sensor designed as a lidar sensor, accumulated in a world coordinate system
  • FIG. 4 schematically shows the measurements from FIG. 1, offset in time and accumulated in the world coordinate system, with a calibrated sensor designed as a lidar sensor, and FIG
  • FIG. 5 schematically an enlarged detail from FIG. 4. Corresponding parts are provided with the same reference symbols in all figures.
  • a method for calibrating a distance-measuring sensor of a vehicle is explained in more detail below with reference to FIGS. 1 to 5.
  • a distance-measuring sensor for example a lidar sensor, ultrasonic sensor, radar sensor or a camera, in particular a stereo camera, is in particular an environment detection sensor of the vehicle.
  • a precise and consistent mapping of an environment of the vehicle is a necessary criterion for safe driving.
  • a precise and consistent representation of the surroundings requires an extrinsic calibration of the sensors, in particular the distance-measuring sensors, of the vehicle to one another or to the vehicle, as well as a temporal calibration, i. H. a synchronization of an internal sensor clock.
  • both calibrations i. H. the extrinsic and temporal calibration
  • a single measurement step d. H. carried out in a single process sequence, advantageously for all distance-measuring sensors of the vehicle.
  • the method is so general and robust that it can be used in almost any surroundings of the vehicle without additional measurement and calibration technology.
  • the minimum requirement is, for example, the presence of at least one static object that can be detected with the sensor in the vicinity of the vehicle. This should be the case in practically every conceivable situation in which the vehicle can find itself, in particular during its own movement.
  • extrinsic transformation T ext is determined for the respective sensor from its sensor coordinate system to a predetermined vehicle coordinate system.
  • the extrinsic transformation T ext is composed of an xyz translation, ie the installation position of the sensor on the vehicle and thus an x coordinate, y coordinate and z coordinate of the installation position of the sensor in the vehicle coordinate system, and an orientation, ie a roll angle R. , Pitch angle and yaw angle G, also referred to as yaw, pitch and roll angle, together.
  • the vehicle has a module which provides movement data in the vehicle coordinate system.
  • the vehicle's own movement is determined by means of this module of the vehicle, also referred to as the self-movement module, and provides corresponding data on this self-movement.
  • Sensor data of the sensor can thus be transformed into the vehicle coordinate system with the extrinsic transformation T ext and into a world-fixed coordinate system, hereinafter referred to as world coordinate system WCS, by means of the intrinsic movement data.
  • the clocks internal to the sensor are also compared at the same time, ie in particular the internal clock of the sensor with a clock of the vehicle's own movement module. Without time-synchronized clocks, it is not possible to create a uniform representation of the surroundings. I. E. it cannot be determined when an object was in which position.
  • the sensor is calibrated relative to the vehicle's own movement, also referred to as ego-motion. If this is not the case, the sensor will deliver different measured values for the same world-fixed object point from different vehicle positions. This applies to all measured / detected world-fixed object points.
  • the world-fixed coordinate system i. H. the world coordinate system WKS
  • cells Z of finite size, for example 10 cm x 10 cm x 10 cm.
  • These occupied cells Z are also referred to as marker cells.
  • a number A of these marker cells is therefore a measure of how well the sensor is calibrated for the vehicle's own movement.
  • the number A of marker cells changes with each parameter change.
  • the measured values for the same world-fixed object point from different positions of the sensor will end up in different cells Z, since due to this poor calibration from different positions of the sensor in the course of the vehicle's own movement for the same world-fixed object point, different measuring positions TMP transformed into the world coordinate system WKS that are far apart, so that there is a high probability that they are in different cells Z.
  • the number A of marker cells thus increases.
  • the number A of marker cells will decrease, since for the respective world-fixed object point, transformed measurement positions TMP that are close together are determined from all positions of the sensor in the course of the vehicle's own movement, which increases the probability that they are in the same cell Z. . Accordingly, the optimum calibration is given when the number A of marker cells is minimal. This is particularly the case when, due to the good calibration, the same transformed measurement position TMP is determined from all positions of the sensor in the course of the vehicle's own movement for the respective world-fixed object point.
  • all distance-measuring sensors for example stereo cameras, lidar sensors, radar sensors and ultrasonic sensors, can be calibrated without additional aids and in almost any environment.
  • An analogous procedure allows the synchronization of the sensor-internal clock and the clock of the self-movement module.
  • the world coordinate system WCS always delivers the same result. If the calibration or the temporal synchronization between the distance-measuring sensor and the vehicle's own movement module is not correct, a new transformed measuring position TMP in the world coordinate system WKS and thus several different ones for the respective world-fixed object point is obtained for each measuring position MP of the world-fixed object point recorded from different sensor positions transformed measuring positions TMP, d. H. with deviating world coordinates, in the world coordinate system WCS.
  • This change in the world coordinates for the same world-fixed object point and the resulting plurality of transformed measuring positions TMP in the world coordinate system WKS for the same world-fixed object point is used in the method described here to calibrate the distance-measuring sensor, in particular to calibrate the vehicle's own movement module.
  • the procedural rule is:
  • the optimum here is that existing objects are represented with as few cells Z as possible, ie several measurements of the same world-fixed object point by means of the sensor at different times during the vehicle's own movement fall into the same cell Z, they advantageously provide the same transformed measurement position TMP.
  • This method specification advantageously results in the method described here for calibrating the distance-measuring sensor of the vehicle, in particular with respect to the vehicle's own movement, in which a transformation parameter value of at least one transformation parameter for a coordinate transformation is thus advantageously determined, with which a measurement position MP determined in the sensor coordinate system is converted into the world coordinate system WCS is transformed.
  • the transformation parameter value of the at least one transformation parameter is determined by an optimization method in which measurement positions MP, which were determined with the sensor at different times during the vehicle's own movement, are evaluated.
  • the optimization method comprises the following steps: a) Transformation of the measurement positions MP with a predetermined transformation parameter value of the at least one transformation parameter into the coordinate grid KG of the world coordinate system WKS, b) Counting the cells Z of the coordinate grid KG to which at least one of the transformed measurement positions TMP is assigned, c ) Repeating steps a) and b) with a transformation parameter value of the at least one transformation parameter modified in each case, ie with each repetition, and determining the transformation parameter value of the at least one transformation parameter, which leads to a minimum in step b), ie to a minimum of the number A. of the cells Z of the coordinate grid KG to which at least one of the transformed measurement positions TMP is assigned.
  • a transformation parameter value is determined for at least one transformation parameter embodied as an extrinsic sensor parameter of the sensor and / or for the transformation parameter embodied as a time offset between the sensor-internal clock of the sensor and the clock of the vehicle's own movement module.
  • the at least one transformation parameter designed as an extrinsic sensor parameter is, for example, the x coordinate, y coordinate or z coordinate of the installation position of the sensor in the vehicle coordinate system or the roll angle R, pitch angle or yaw angle G of the sensor with respect to the vehicle coordinate system.
  • transformation parameter values of several transformation parameters for example all extrinsic sensor parameters and, for example, additionally the time offset between the sensor-internal clock of the sensor and the clock of the vehicle's own movement module, are advantageously used, determined for the coordinate transformation with which a measurement position MP determined in the sensor coordinate system is transformed into the world coordinate system WCS.
  • transformation parameter values of several transformation parameters for example all extrinsic sensor parameters and, for example, additionally the time offset between the sensor-internal clock of the sensor and the clock of the vehicle's own movement module
  • Transformation parameter value determined for the respective transformation parameter The transformation parameter values of the transformation parameters are determined by the optimization method in which measurement positions MP that were determined with the sensor at different times during the vehicle's own movement are evaluated.
  • the optimization process accordingly comprises the following steps: a) Transformation of the measurement positions MP with a predetermined transformation parameter value of the respective transformation parameter into the coordinate grid KG of the world coordinate system WKS, b) Counting the cells Z of the coordinate grid KG to which at least one of the transformed measurement positions TMP is assigned, c ) Repeating steps a) and b) with in each case, d. H. at each repetition, modified transformation parameter values of the transformation parameters and determining the transformation parameter values of the transformation parameters which lead to a minimum in step b), d. H.
  • Transformation parameter value of several or all transformation parameters is modified at the same time.
  • the method can be used for any distance measuring sensor, for example for lidar sensors, stereo cameras, radar sensors and ultrasonic sensors.
  • the method is also robust against distance noise from individual point measurements.
  • the method enables fast end-of-line calibration.
  • end-of-line calibration also referred to as end-of-line calibration.
  • the method is thus used to carry out the calibration of the distance-measuring sensor or of the respective distance-measuring sensor of the vehicle at a production line end of the vehicle. Instead of laboriously measuring the vehicle, it is sufficient to drive the vehicle a few meters using the method. This can significantly accelerate the process chain.
  • the end-of-line calibration is one of the most time-consuming steps in vehicle construction.
  • Another use of the method is, for example, online calibration and / or decalibration detection.
  • the calibration by means of the method is thus advantageously carried out during regular ferry operation of the vehicle.
  • the method can be used to continuously perform the calibration of the distance-measuring sensor or the respective distance-measuring sensor of the vehicle while the vehicle is in motion and / or to detect whether the distance-measuring sensor or the respective distance-measuring sensor of the vehicle is decalibrated, for example by a mechanical defect.
  • Another use of the method is, for example, offline calibration for verification and / or HD map generation, that is to say the creation of a high-resolution digital map.
  • the method can for example be applied to recorded sequences in order to obtain a high-precision calibration. This can be used to serve as a reference for an online calibration. Furthermore, this calibration can be used for the construction of high-resolution digital maps.
  • FIGS. 1-10 An example of the implementation of the method by means of a distance-measuring sensor of the vehicle designed as a lidar sensor is shown on the basis of FIGS.
  • real data from the surroundings of the vehicle are recorded using this sensor, with dynamic objects also being present in the surrounding area and being recorded as well.
  • FIG. 1 shows, in a highly schematic manner, a point cloud sequence recorded by the sensor, which was transformed into the world coordinate system WKS with the aid of the own movement data and quantized in cells Z of 10 cm ⁇ 10 cm ⁇ 10 cm.
  • the recorded measurement positions MP were transformed according to step a) of the method with a predetermined transformation parameter value of the respective transformation parameter into the coordinate grid KG of the world coordinate system WKS shown in FIG. 1 with cells Z of 10 cm ⁇ 10 cm ⁇ 10 cm.
  • step b) of the method the cells Z of the coordinate grid KG to which at least one of the transformed measurement positions TMP is assigned are counted. Then, in step c) of the method, steps a) and b) are repeated with respectively modified transformation parameter values of the transformation parameters and the transformation parameter values of the transformation parameters are determined which lead to a minimum in step b), ie to a minimum of the number A of cells Z of the coordinate grid KG to which at least one of the transformed measurement positions TMP is assigned.
  • FIGS. 2 and 3 This is shown in FIGS. 2 and 3 for the change in the extrinsic transformation matrix for this sequence by adapting the yaw angle G (FIG. 2) and roll angle R (FIG. 3).
  • the transformation parameter values for the extrinsic sensor parameter yaw angle G are shown as transformation parameters on the abscissa axis in FIG. 2 and the transformation parameter values for the extrinsic sensor parameter roll angle R as transformation parameters in FIG . H. of the cells Z of the coordinate grid KG to which at least one of the transformed measurement positions TMP is assigned.
  • Figure 4 and Figure 5 as a detail from Figure 4 show the result of adapting the transformation parameters, here in particular the extrinsic sensor parameters of the extrinsic matrix, with the optimal angle values of the yaw angle G and roll angle R determined in this way and transferring the point measurements to the world coordinate system WKS.
  • the transformation parameters here in particular the extrinsic sensor parameters of the extrinsic matrix
  • the optimal angle values of the yaw angle G and roll angle R determined in this way and transferring the point measurements to the world coordinate system WKS.

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Abstract

L'invention concerne un procédé d'étalonnage d'un capteur de mesure de distance d'un véhicule, plus particulièrement en ce qui concerne un déplacement effectué par le véhicule. Selon l'invention, une valeur de paramètre de transformation d'au moins un paramètre de transformation est déterminée pour une transformation de coordonnées, valeur au moyen de laquelle une position de mesure (MP) déterminée dans un système de coordonnées de capteur est transformée en un système de coordonnées universelles (WKS), la valeur de paramètre de transformation du ou des paramètres de transformation étant déterminée au moyen d'un procédé d'optimisation dans lequel sont évaluées des positions de mesure (MP) qui ont été déterminées par le capteur à différents moments au cours du déplacement individuel du véhicule, le procédé d'optimisation comprenant les étapes suivantes consistant à : a) transformer les positions de mesure (MP) à l'aide d'une valeur de paramètre de transformation prédéfinie du ou des paramètres de transformation en une grille de coordonnées (KG) du système de coordonnées universelles (WKS), b) compter les cellules (Z) de la grille de coordonnées (KG), cellules auxquelles est associée au moins une des positions de mesure transformées (TMP), c) répéter les étapes a) et b) utiliser, dans chaque cas, une valeur de paramètre de transformation modifiée du ou des paramètres de transformation et déterminer la valeur de paramètre de transformation du ou des paramètres de transformation qui conduit à un minimum à l'étape b).
PCT/EP2020/078589 2019-12-02 2020-10-12 Procédé d'étalonnage d'un capteur de mesure de distance d'un véhicule WO2021110303A1 (fr)

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