Method and calibration system for calibrating autonomous mobile machine

Abstract

In order to calibrate the autonomous mobile machine, by means of its machine self-calibration, it is proposed that: lt; 1gt; for example, "Automated Guided Vehicle Fat; AGVgt; the invention relates to an autonomous mobile machine (AMM) comprising a mobile base unit (MBU) and a 6D motion controlled manipulator (MPL) capable of performing a motion of six degrees of freedom lt, DOFgt, in space, and equipped with a sensor device (SD), such as a laser scanner (LS), attached to the mobile base unit (MBU); lt; 2gt; (tk) a series of measurements (MMS) of calibration objects (COB, COBcs, CHE) with a sensor device (SD) to provide sensor device data (SDDT), rigidly attaching (att) the calibration objects (COB, COBcs, CHE) to a 6D motion controlled manipulator (MPL), the calibration objects being movable in a sensor device field-of-view plane (SDFVP) preferably regarded as a 2D slice of a 3D environment according to the 6D motion or corresponding 6DOF motion of the manipulator (MPL), and lt; iigt, iigt; an accurate estimate of a mounting pose (MP, MP3D, MP6D) of a sensor device (SD, LS) is calculated (cmp) for calibrating an autonomous mobile machine (AMM) based on geometry data (GDT) of a calibration object (COB, COBcs, CHE), motion data (MDT) of a manipulator (MPL), and sensor device data (SDDT).

Description

Field of the Invention

[0001] The present invention relates to a method for calibrating an autonomous mobile machine according to the preamble of claim 1 and a calibration system for calibrating an autonomous mobile machine according to the preamble of claim 8. Background Art

[0002] The present application solves the problem of automatically measuring the mounting position of a sensor device (e.g., a laser scanner) attached to an autonomous mobile machine, which is preferably designed as an "automated guided vehicle" <agv>” or a mobile robot. An autonomous mobile machine typically consists of a mobile base unit and is capable of performing "6 degrees of freedom" in space <dof>is composed of a 6D motion-controlled manipulator (e.g., a robotic arm) for "movement" and is equipped with a sensor device, or a corresponding laser scanner, which is attached to the mobile base unit.

[0003] For the reliable and accurate operation of an autonomous mobile machine, especially for docking maneuvers that require high positioning accuracy, it is necessary to precisely measure the installation position of the sensor device. However, due to the typically large construction tolerances in autonomous mobile machines, precise data is not always obtainable. In addition, the installation position of the sensor device may also change during operation after initial construction and commissioning, for example, due to collisions or maintenance (e.g., replacing the sensor device). Precisely measuring the installation position of the sensor device in an autonomous mobile machine is a complex and time-consuming task.

[0004] According to the prior art, a rough estimate of the installation position of the sensor device in an autonomous mobile machine is typically obtained based on construction blueprints. This initial estimate is usually adjusted in an iterative process, thus using certain software for visualizing the sensor device data to verify the correctness of the measurement data after adjusting the installation position parameters.

[0005] There are known methods for automatically measuring the position of the sensor device in an autonomous mobile machine. These methods are based on detecting objects in a series of measurements. These measurements are typically carried out by placing some calibration objects in the field of view of the sensor device in a predetermined configuration and moving the autonomous mobile machine in a certain predetermined pattern so that the calibration objects can be measured by the sensor device from multiple viewpoints. The geometric configuration of the objects detected through multiple measurements, together with the data on the movement of the automated machine, is used to establish an optimization problem. Based on the solution of this optimization problem, the position of the sensor device is obtained.

[0006] These methods have three significant drawbacks.

[0007] First, they rely on the estimate of the autonomous mobile machine regarding its own movement, which is typically inaccurate and has incremental errors, resulting in imprecise results.

[0008] Second, free space is required for placing the calibration objects and moving the AGV. Ideally, only the calibration objects should be in the field of view of the sensor device during the calibration process, and since these objects must be measured from multiple viewpoints, some space is needed for maneuvering the autonomous mobile machine. Such free space is not always available in the operating environment of the autonomous mobile machine.

[0009] Third, these methods only calculate the pose and orientation of the sensor device, i.e., it is assumed that they are horizontally and vertically aligned. These methods cannot estimate the complete 6D position of the sensor device. Summary of the Invention

[0010] An object of the present invention is to provide a method and a calibration system for calibrating an autonomous mobile machine, by which the machine can perform self-calibration.

[0011] This object is solved by the features in the characterizing part of claim 1 for the method defined in the preamble of claim 1.

[0012] This object is further solved by the features in the characterizing part of claim 8 for the calibration system defined in the preamble of claim 8.

[0013] According to claims 1 and 8, the main idea of the present invention is to utilize a calibration object that can be easily detected by a sensor device, in particular a laser scanner, which is attached to or housed in the autonomous mobile machine to be self-calibrated, and the autonomous mobile machine is preferably designed as an "automated guided vehicle" <agv>", the calibration object actively moves within the 3D environment in front of the sensor device by means of the manipulator (e.g., robotic arm) of the autonomous mobile machine for automatically and precisely measuring the mounting pose (combination of position and orientation) of the sensor device. To calibrate the autonomous mobile machine, the calibration object is rigidly attached to the manipulator and automatically moved by the manipulator such that the calibration object is detected by the sensor device. By fusing the geometric data of the calibration object, the motion data of the manipulator, and the sensor device data provided by the sensor device when detecting the calibration object, an accurate estimate of the mounting pose of the sensor device is automatically calculated and even preferably verified.

[0014] According to this concept, the implementation of calibrating the autonomous mobile machine is carried out in the following manner: (i) The autonomous mobile machine includes a mobile base unit and is capable of performing "6 degrees of freedom" in space <dof>a 6D motion-controlled manipulator for "motion", and equipped with a sensor device attached to a mobile base unit, (ii)Perform a series of measurements on the calibration object using the sensor device to provide sensor device data, (iii)Rigidly attach the calibration object to the 6D motion-controlled manipulator, which can move within the field-of-view plane of the sensor device according to the 6D motion or the corresponding 6DOF motion of the manipulator. The field-of-view plane of the sensor device is preferably regarded as a 2D slice of a 3D environment, (iv)Based on the geometric data of the calibration object, the motion data of the manipulator, and the sensor device data, calculate an accurate estimate of the mounting pose of the sensor device for calibrating the autonomous mobile machine.

[0015] The method outlined above differs from known solutions, such as those discussed in the introduction section, in that the manipulator of the autonomous mobile machine moves the calibration object, whereas according to known solutions, this is done in the opposite way, where the autonomous mobile machine moves around a number of calibration objects.

[0016] Compared with the prior art, the proposed method has several advantages: - Therefore, calibration based on full 6D is possible. By utilizing all degrees of freedom of motion, the 6D motion-controlled manipulator can perform a full 6D mounting pose of the sensor device, which can be correspondingly estimated, rather than just the "2D plus orientation" values typically estimated by solutions according to the prior art; - Only minimal space and construction requirements are needed. By moving the calibration object around the autonomous mobile machine equipped with the sensor device, rather than moving the autonomous mobile machine around a number of calibration objects, the proposed method has minimal space and environmental construction requirements. Calibration can be performed at the operation site without the need for a large area that must be blocked during calibration; - The calibration process is faster because when the calibration object moves around the autonomous mobile machine equipped with the sensor device, the calibration process is shorter compared to moving the entire autonomous mobile machine equipped with the sensor device around the calibration object; - The calibration process is more accurate. Therefore, the motion of the manipulator is generally more accurate than the motion of the autonomous mobile machine. This is utilized in the optimization process that formulates an optimization problem (see claims 3 and 9) to obtain more accurate results. In addition, since all degrees of freedom of motion that the 6D motion-controlled manipulator can perform allow the generation of detection trajectories, the detection trajectory has richer information compared to the detection trajectories that can be obtained when the entire autonomous mobile machine moves around the calibration object.

[0017] Advantageous refinements of this concept on which the invention is based are given by dependent claims 2 to 7 or the corresponding dependent claims 9 to 14.

[0018] Thus, according to claims 2 and 9, it is advantageous if the calibration object has a certain geometry with which an exact estimate of the mounting pose in a measurement series for a given measurement configuration can be analytically calculated.

[0019] In this context, the advantages are: (i) according to claim 5 or the corresponding claim 12, if the calibration object has a certain material and shape with which the calibration object can be easily and correctly detected by the sensor device; and (ii) according to claims 6 and 7 or the corresponding claims 13 and 14, if the calibration object is used as a conical calibration object or as a handheld device having a handle and a conical calibration head, which handheld device is a connected or formed dual-functional part, wherein when using an optimization process for establishing an optimization problem, a circle fitting algorithm can be applied to estimate the diameter of the conical calibration object and the information associated with this estimate is used to improve the optimization problem of the optimization process.

[0020] For applying an optimization process for establishing an optimization problem, it is advantageous according to claims 3 and 10: (i) to create a detection trajectory based on sensor device data and geometric data by moving the calibration object within the field-of-view plane of the sensor device using a 6D motion-controlled manipulator, wherein due to this movement, the detection trajectory provides the 2D pose of the calibration object relative to the sensor device; (ii) to match the detection trajectory with a reference trajectory calculated using the geometric data of the calibration object and the motion data of the 6D motion-controlled manipulator; (iii) the matched trajectory is used in the optimization process, wherein the result of the optimization problem corresponds to an exact estimate of the 3D mounting pose or the 6D mounting pose of the sensor device for calibrating an autonomous mobile machine.

[0021] According to claims 5 and 11, the 3D mounting pose or the 6D mounting pose of the sensor device along the longitudinal axis and the transverse axis can be advantageously estimated by controlling the intersection point with the field-of-view plane of the sensor device due to moving the calibration object in the vertical direction into the field-of-view plane of the sensor device. Description of the Drawings

[0022] In addition to the above, further advantageous refinements of the invention result from the following description of preferred embodiments of the invention according to Figures 1 to 9 which show: Figure 1 is an autonomous mobile machine that self-calibrates within a calibration system equipped with a sensor device, Figure 2 is an autonomous mobile machine that self-calibrates within a calibration system with a field-of-view plane of the sensor device, Figure 3 is a calibration system for self - calibrating an autonomous mobile machine by attaching a calibration object to a manipulator of the autonomous mobile machine according to Figure 1 the autonomous mobile machine, Figure 4 is a calibration system for self - calibrating an autonomous mobile machine, wherein the attached calibration object according to Figure 3 intersects the field - of - view plane of the sensor device according to Figure 2 the sensor device. Figure 5 is a calibration system for self - calibrating an autonomous mobile machine according to Figure 4 wherein the attached calibration object intersects the field - of - view plane of the sensor device, thereby creating a detection trajectory by moving the calibration object within the field - of - view plane of the sensor device. Figure 6 is a calibration system for self - calibrating an autonomous mobile machine according to Figure 4 and Figure 5 wherein the attached calibration object intersects the field - of - view plane of the sensor device to allow an estimation of the mounting pose of the sensor device along the longitudinal axis. Figure 7 is a calibration system for self - calibrating an autonomous mobile machine according to Figure 4 and Figure 5 wherein the attached calibration object intersects the field - of - view plane of the sensor device to allow an estimation of the mounting pose of the sensor device along the transverse axis. Figure 8 is a conical calibration object through which, when changing the height at which the cone intersects the laser field of view, arcs of different diameters are obtained, or when tilting the cone, ellipses with changing axis lengths are obtained. Figure 9 is a flow chart providing an accurate estimation of the mounting pose of the sensor device for calibrating the Figure 4 and Figure 5 autonomous mobile machine depicted in DETAILED DESCRIPTION

[0023] Figure 1 shows an autonomous mobile machine AMM self - calibrating within a calibration system CBS. For example, an "Automated Guided Vehicle" <agv>” and an autonomous mobile machine AMM that is part of the calibration system CBS includes a mobile base unit MBU and is capable of performing "6 degrees of freedom" in space <dof>a 6D motion-controlled manipulator MPL for "movement", and is equipped with a sensor device SD. The sensor device SD is preferably a laser scanner LS and is attached to the mobile base unit MBU. The sensor device SD is used for the positioning and navigation of the autonomous mobile machine AMM. Although Figure 1 only one sensor device SD is shown, the autonomous mobile machine AMM may also contain more than one sensor device SD.

[0024] To control the 6D motion or the corresponding 6DOF motion of the manipulator MPL and the mobility of the autonomous mobile machine AMM, a control unit CTU is included in the mobile base unit MBU. In addition to this control unit CTU, the mobile base unit MBU also includes a computing unit CPU and a data storage medium DSTM. The computing unit CPU, the sensor device SD, LS, the control unit CTU, and the data storage medium DSTM form a functional structure FST for the self-calibration of the autonomous mobile machine AMM. The relevance of the functional structure FST regarding the self-calibration of the autonomous mobile machine AMM will be described later for Figure 4 and Figure 5 description.

[0025] Figure 2 In addition to Figure 1 the autonomous mobile machine AMM that self-calibrates within the calibration system CBS, a depiction of the sensor device field-of-view plane SDFVP is also shown. This sensor device field-of-view plane is a 2D slice of the 3D environment that spans the longitudinal and lateral axes of the sensor device SD that are substantially in front of the sensor device SD, LS. How the 2D slice cuts the 3D environment depends on the mounting pose of the sensor device SD attached to the mobile base unit MBU.

[0026] Figure 3 In addition to Figure 1 the autonomous mobile machine AMM that self-calibrates within the calibration system CBS, a depiction of a calibration object COB, which is another part of the calibration system CBS, is also shown. This calibration object is rigidly attached att to the 6D motion-controlled manipulator MPL and can be moved within the sensor device field-of-view plane SDFVP in consideration of the 6D motion or the corresponding 6DOF motion of the manipulator MPL controlled by the control unit CTU according to the depiction in Figure 2 (see Figure 4 and Figure 5 ).

[0027] The calibration object COB has a certain material and shape, by means of which the calibration object COB can be easily and correctly detected by the sensor device. Therefore, the calibration object COB is advantageously designed as a handheld device HHD having a handle HDL and a conical calibration head CHE. The length and shape of the handle HDL depend on the range or reach of the manipulator MPL and the attachment device, such as a fixture. Importantly, the conical calibration head CHE, which is conical, can be moved within the sensor device field-of-view plane SDFVP. Alternatively, the calibration object COB can preferably be designed as a conical calibration object COB CS 。

[0028] Figure 4 In Figures 1 to 3 the context of which is shown a calibration system CBS of a self-calibrating autonomous mobile machine AMM according to Figure 3 in which the calibration object COB, COB CS 、CHE is attached att to a 6D motion-controlled manipulator MPL and can be moved according to the 6D motion or the corresponding 6DOF motion of the manipulator MPL controlled by a control unit CTU, and thereby intersects the sensor device field-of-view plane SDFVP according to Figure 2 。

[0029] In this system constellation, the sensor device SD, LS performs a tk measurement series MMS on the calibration object COB, COB CS 、CHE, wherein, due to the measurement series MMS, sensor device data SDDT is provided. The provided sensor device data SDDT is input into a computing unit CPU for further processing for the self-calibration of the autonomous mobile machine AMM.

[0030] In this context, the data storage medium DSTM already mentioned with respect to Figure 1 is also used to store the geometric data GDT of the calibration object COB, COB CS 、CHE and the motion data MDT related to the motion of the 6D motion-controlled manipulator MPL or the corresponding 6DOF motion. As the sensor device data SDDT, the mentioned data GDT, MDT are also input into the computing unit CPU.

[0031] Based on the input geometric data GDT, the input motion data MDT and the input sensor device data SDDT, the computing unit CPU of the formed functional structure FST for the self-calibration of the autonomous mobile machine AMM calculates cmp an accurate estimate of the mounting pose MP of the sensor device SD, LS for calibrating the autonomous mobile machine AMM.

[0032] The calibration object COB, COB CS , CHE preferably has a certain geometric shape, and by using this geometric shape, the installation poses MP, MP in the measurement series MMS for a given measurement configuration are analytically calculated. 3D , MP 6D for an accurate estimate.

[0033] Figure 5 Based on Figure 4 The depiction in shows the calibration system CBS of the self - calibrating autonomous mobile machine AMM, where the attached calibration objects COB, COB CS , CHE intersect with the sensor device field - of - view plane SDFVP, and thus by moving the calibration objects COB, COB CS , CHE within the sensor device field - of - view plane SDFVP, a detection trajectory DTR is created.

[0034] For this purpose, the calculation unit CPU is designed such that a detection trajectory DTR based on sensor device data SDDT and geometric data GDT is created, where due to the movement of the calibration objects COB, COB CS , CHE, the detection trajectory DTR provides the 2D pose of the calibration objects COB, COB CS , CHE relative to the sensor devices SD, LS.

[0035] The calculation unit CPU is also designed such that the created detection trajectory DTR matches a reference trajectory RTR calculated using the geometric data GDT of the calibration objects COB, COB CS , CHE and the motion data MDT of the 6D motion - controlled manipulator MPL.

[0036] In addition, the calculation unit CPU is designed such that an optimization process OPP (see Figure 9 ) for establishing an optimization problem is applied by using the matching trajectories DTR, RTR, where the result of this optimization problem provides an accurate estimate of the installation pose MP of the sensor devices SD, LS, and corresponds to an accurate estimate of the 3D installation pose MP 3D of the sensor devices SD, LS or an accurate estimate of the 6D installation pose MP 6D for calibrating the autonomous mobile machine AMM.

[0037] Furthermore, when using a handheld device HHD having a handle HDL and a conical calibration head CHE as a connecting or forming dual - function part or alternatively using a conical calibration object COB CS , and when the calculation unit CPU is designed such that a circle - fitting algorithm is used in the calculation unit CPU to estimate the diameter of the conical calibration head CHE or the corresponding conical calibration objects COB, COB CS , CHE, the optimization problem of the optimization process can be improved by this estimated diameter information.

[0038] The key insight in all of this is that the calculation unit CPU uses the calibration object COB, COB CS The reference trajectory RTR calculated from the geometrical data GDT of the CHE and the kinematic data MDT of the 6D-motion controlled manipulator MPL (these data are based on very precise 6D motions or respectively 6DOF motions performed by the manipulator MPL under the control of the control unit CTU) can be regarded as "real" or "ground truth" data. Differences compared to the sensor device data SDDT are due to sensor device noise and inaccurate mounting poses of the sensor devices SD, LS, which are subsequently corrected by an optimization process.

[0039] Figure 6 Shown according to Figure 4 and Figure 5 Calibration system CBS of self-calibration autonomous mobile machine AMM, wherein the attached calibration object COB, COB CS , CHE intersects with the sensor device field of view plane SDFVP to allow estimation of the 3D installation pose MP of the sensor device SD, LS along the longitudinal axis 3D Or 6D installation pose MP 6D .

[0040] Figure 7 Shown according to Figure 4 and Figure 5 Calibration system CBS of self-calibration autonomous mobile machine AMM, wherein the attached calibration object COB, COB CS , CHE intersects with the sensor device field of view plane SDFVP to allow estimation of the 3D installation pose MP of the sensor device SD, LS along the transverse axis 3D Or 6D installation pose MP 6D .

[0041] The kinematic degrees of freedom of the 6D kinematically controlled manipulator MPL device can advantageously be used to generate a detection trajectory DTR containing additional information to be considered in the optimization problem of the optimization process OPP (see Figure 9 ).

[0042] Therefore, the calibration object COB, COB CS CHE can be based on Figure 5 Move in the vertical direction VD to control the intersection with the laser scanner field of view plane SDFVP. In this way, the 3D installation posture MP of the sensor device SD, LS can be calculated 3D An accurate estimate or 6D installation pose MP 6D accurate estimate of .

[0043] Figure 6 and Figure 7 illustrates how moving calibration objects COB, COB CS , CHE in the vertical direction VD can be used to control the intersection with the field-of-view plane SDFVP and thereby allow an estimation of the 3D mounting pose MP of the sensor device SD, LS along the longitudinal axis (i.e., roll effect; see Figure 6 ) and the lateral axis (i.e., pitch effect; see Figure 7 ). 3D or the 6D mounting pose MP 6D .

[0044] Figure 8 shows a conical calibration object COB CS , by which, when changing the height at which the cone intersects the field of view of the laser, arcs of different diameters are obtained, or when tilting the cone, ellipses with changing axis lengths are obtained.

[0045] By doing so, and due to the geometry of the conical calibration object COB CS , it is beneficial that an accurate estimation of the mounting poses MP, MP 3D , MP 6D in the measurement series MMS for a given measurement setup can be analytically calculated.

[0046] Figure 9 shows a flow chart for providing an accurate estimation of the mounting pose MP of the sensor device SD, LS, said accurate estimation corresponding to the accurate estimation of the 3D mounting pose MP 3D of the sensor device SD, LS or the accurate estimation of the 6D mounting pose MP 6D for calibration Figure 4 and Figure 5 the autonomous mobile machine AMM depicted and correspondingly described in< / dof> < / agv> < / dof> < / agv> < / dof> < / agv>

Claims

1. A method for calibrating an autonomous mobile machine, by which method: - An autonomous mobile machine (AMM) with a mobile base unit (MBU) and a 6D motion-controlled manipulator (MPL), in particular an "automated guided vehicle" <agv>", capable of performing "6 degrees of freedom" in space <dof>"movement", and is equipped with a sensor device (SD), in particular a laser scanner (LS), which sensor device is attached to the mobile base unit (MBU), < / dof> < / agv> - Using the sensor device (SD) to perform a measurement series (MMS) (tk) on a calibration object (COB, COB CS , CHE). - Due to the measurement series (MMS), sensor device data (SDDT) is provided, It is characterized in that: - Rigidly attach the calibration object (COB, COB CS , CHE) to the 6D motion-controlled manipulator (MPL), and the calibration object is movable within the sensor device field-of-view plane (SDFVP) according to the 6D motion or corresponding 6DOF motion of the manipulator (MPL), and the sensor device field-of-view plane is particularly regarded as a 2D slice of the 3D environment, - Based on the geometric data (GDT) of the calibration object (COB, COB CS , CHE), the motion data (MDT) of the manipulator (MPL), and the sensor device data (SDDT), calculate (cmp) an accurate estimate of the mounting pose (MP, MP 3D , MP 6D ) of the sensor device (SD, LS) for calibrating the autonomous mobile machine (AMM).

2. The method according to claim 1, wherein The calibration object (COB, COB CS , CHE) has a geometry, and using the geometry, an accurate estimate of the mounting pose (MP, MP 3D , MP 6D ) in the measurement series (MMS) for a given measurement configuration is analytically calculated.

3. The method according to claim 1 or 2, characterized in that, - By moving the calibration object (COB, COB CS , CHE) within the sensor device field of view plane (SDFVP) using the 6D motion controlled manipulator (MPL), a detection trajectory (DTR) based on the sensor device data (SDDT) and the geometric data (GDT) is created, wherein, due to the movement, the detection trajectory (DTR) provides the 2D pose of the calibration object (COB, COB CS , CHE) relative to the sensor device (SD). - The detected trajectory (DTR) matches a reference trajectory (RTR) calculated using the geometric data (GDT) of the calibration object (COB, COB CS , CHE) and the motion data (MDT) of the 6D motion-controlled manipulator (MPL). - By using a matching trajectory (DTR, RTR) to apply an optimization process (OPP) for establishing an optimization problem, Among them, the result of the optimization problem corresponds to the precise estimation of the 3D mounting pose (MP 3D of the sensor device (SD, LS) or the precise estimation of the 6D mounting pose (MP 6D ) for calibrating the autonomous mobile machine (AMM).

4. The method according to claim 3, characterized in that, By controlling the intersection point with the sensor device field of view plane (SDFVP) by moving the calibration object (COB, COB CS , CHE) in the vertical direction (VD) to the sensor device field of view plane (SDFVP), estimate the 3D mounting pose (MP 3D ) or 6D mounting pose (MP 6D ) of the sensor device (SD, LS) along the longitudinal axis and the transverse axis.

5. The method according to any one of claims 1 to 4, characterized in that, The calibration object (COB, COB CS , CHE) has a material and a shape, and by using the material and the shape, the calibration object (COB, COB CS , CHE) can be easily and correctly detected by the sensor device (SD, LS).

6. The method according to claim 1 or 2, characterized in that, The calibration object (COB, COB CS , CHE) is used as a conical calibration object (COB CS ) or is a hand-held device (HHD) having a handle (HDL) and a conical calibration head (CHE), and the hand-held device is a connected or formed dual-functional part.

7. The method according to claim 3 or 4, characterized in that, - The calibration object (COB, COB CS , CHE) is used as a conical calibration object (COB CS ) or is a hand-held device (HHD) having a handle (HDL) and a conical calibration head (CHE), the hand-held device being a connected or formed dual-functional part, - Use a circle fitting algorithm to estimate the diameter of the conical calibration object or conical calibration head (COB, COB CS , CHE), wherein the information related to the estimation is used to improve the optimization problem of the optimization process (OPP).

8. A calibration system (CBS) for calibrating an autonomous mobile machine, having: - Autonomous Mobile Machine (AMM), in particular "Automated Guided Vehicle" <agv>", the autonomous mobile machine includes a mobile base unit (MBU) and is capable of performing "6 degrees of freedom" in space <dof>A 6D motion-controlled manipulator (MPL) for "movement", < / dof> < / agv> - A sensor device (SD), in particular a laser scanner (LS), which sensor device is attached to the mobile base unit (MBU), - Calibration objects (COB, COB CS , CHE), for which a measurement series (MMS) (tk) is carried out using the sensor device (SD, LS), where, since The measurement series (MMS), providing sensor device data (SDDT), It is characterized in that: - The calibration object (COB, COB CS , CHE) is rigidly attached (att) to the 6D motion-controlled manipulator (MPL) and is movable within the sensor device field-of-view plane (SDFVP) according to the 6D motion or the corresponding 6DOF motion of the manipulator (MPL), the sensor device field-of-view plane being regarded in particular as a 2D slice of the 3D environment, - A computing unit (CPU) that calculates (cmp) an accurate estimate of the mounting pose (MP, MP CS , MP 3D , MP 6D ) of the sensor device (SD, LS) based on the geometric data (GDT) of the calibration object (COB, COB CS , CHE) input into the computing unit (CPU), the motion data (MDT) of the manipulator (MPL), and the sensor device data (SDDT) for calibrating the autonomous mobile machine (AMM).

9. The calibration system (CBS) according to claim 8, characterized in that, The calibration object (COB, COB CS , CHE) has a geometry, and using the geometry, an accurate estimate of the mounting poses (MP, MP 3D , MP 6D ) in the measurement series (MMS) for a given measurement configuration is analytically calculated.

10. The calibration system (CBS) according to claim 7 or 8, characterized in that, The computing unit (CPU) is designed such that: - Moving the calibration object (COB, COB CS , CHE) within the sensor device field of view plane (SDFVP) by using the 6D motion controlled manipulator (MPL) to create a detection trajectory (DTR) based on the sensor device data (SDDT) and the geometric data (GDT), wherein, due to the movement, the detection trajectory (DTR) provides the 2D pose of the calibration object (COB, COB CS , CHE) relative to the sensor device (SD, LS), - The detected trajectory (DTR) matches the reference trajectory (RTR) calculated using the geometric data (GDT) of the calibration object (COB, COB CS , CHE) and the motion data (MDT) of the 6D motion-controlled manipulator (MPL). - By using a matching trajectory (DTR, RTR) to apply an optimization process (OPP) for establishing an optimization problem, Among them, the result of the optimization problem corresponds to an accurate estimation of the 3D installation pose (MP 3D ) of the sensor device (SD, LS) or an accurate estimation of the 6D installation pose (MP 6D ) for calibrating the autonomous mobile machine (AMM).

11. The calibration system (CBS) according to claim 10, characterized in that, The computing unit (CPU) is designed such that by controlling the intersection point of the sensor device field of view plane (SDFVP) due to moving the calibration object (COB, COB CS , CHE) in the vertical direction (VD) to the sensor device field of view plane (SDFVP), the 3D mounting pose (MP 3D ) or 6D mounting pose (MP 6D ) of the sensor device (SD, LS) along the longitudinal axis and the transverse axis is estimated.

12. The calibration system (CBS) according to any one of claims 8 to 11, characterized in that, The calibration object (COB, COB CS , CHE) has a material and a shape, and by using the material and the shape, the calibration object (COB, COB CS , CHE) can be easily and correctly detected by the sensor device (SD, LS).

13. The calibration system (CBS) according to claim 8 or 9, characterized in that, The calibration object (COB, COB CS , CHE) is used as a conical calibration object (COB CS ) or as a hand-held device (HHD) having a handle (HDL) and a conical calibration head (CHE), the hand-held device being a connected or formed dual-functional part.

14. The calibration system (CBS) according to any one of claims 10 or 11, characterized in that, - The calibration object (COB, COB CS , CHE) is used as a conical calibration object (COB CS ) or is a hand-held device (HHD) having a handle (HDL) and a conical calibration head (CHE), the hand-held device being a connected or formed dual-functional part, - The computing unit (CPU) is designed such that a circle fitting algorithm is used in the computing unit (CPU) to estimate the diameter of the conical calibration object or conical calibration head (COB, COB CS , CHE), wherein the information related to this estimate is used to improve the optimization problem of the optimization process (OPP).

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