Industrial unmanned aerial vehicle post-assembly multi-sensor joint calibration method and calibration tool thereof

Abstract

This application discloses a multi-sensor joint calibration method for industrial UAVs after final assembly, belonging to the field of industrial UAV calibration technology. This method fixes the UAV under test in a single clamping operation, utilizes a multi-attitude flipping mechanism to provide a standard attitude, and combines an orientation reference module to provide a unified heading reference. It completes the acquisition and coupled solution of multi-source data from IMU, magnetic compass, RTK, vision module, and ranging module within the same overall coordinate system, automatically generating and writing a complete set of compensation parameters, and simultaneously generating a calibration report with bound device identification. The accompanying tooling enables full sensor joint calibration to be completed in a single clamping operation. This invention improves calibration accuracy, consistency, and traceability, and is suitable for factory calibration, return-to-factory recalibration, and multi-mounted UAV adaptation for industrial UAVs, possessing promising prospects for industrial application.

Description

Technical Field

[0001] This application relates to the field of industrial drone calibration technology, and in particular to a multi-sensor joint calibration method for industrial drones after final assembly. Background Technology

[0002] As industrial drones are increasingly used in cleaning, hoisting, inspection, firefighting, and surveying, overall assembly quality and flight consistency are becoming key factors affecting delivery efficiency and operational reliability. For industrial drones equipped with flight control and inertial navigation modules, magnetic heading modules, RTK orientation modules, vision-assisted positioning modules, and ranging modules, even after each sensor passes module-level factory testing, new comprehensive deviations may still occur in the overall assembled state due to frame machining tolerances, installation angle errors, clamping stress, cable traction, changes in the electromagnetic environment, and changes in the relative positions of the modules. These deviations are usually not caused by a single sensor itself, but rather originate from assembly coupling errors between the sensor and the aircraft coordinate system, between sensors themselves, and between the sensor and the operational environment.

[0003] Typical post-assembly calibration methods often involve manually moving the entire drone, switching test software individually, and performing single-item calibrations on the inertial navigation, magnetic compass, RTK, vision module, and ranging module. For large industrial drones with high payloads and numerous subsystems, this method struggles to guarantee consistent attitude and orientation during each setup, making the calibration results highly dependent on operator experience. Furthermore, different sensors often use different calibration benchmarks and software tools, making it difficult to establish a unified coordinate relationship between magnetic heading, RTK heading, and externally involved visual ranging directions. This negatively impacts overall flight control, near-wall distance control, hovering stability, and operational safety boundaries.

[0004] Furthermore, in the existing assembly and calibration process, parameter acquisition, compensation calculation, parameter write-back, and report management are usually completed in different stages, resulting in problems such as repeated clamping, repeated positioning, repeated data entry, and broken traceability chains. This is detrimental to batch delivery at the manufacturing end, return-to-factory re-inspection, and after-sales recalibration. Especially in industrial drones used for cleaning, hoisting, and near-wall inspection, if the coordinate relationships of the multi-sensor system at the overall assembly level are not uniformly calibrated, it can easily lead to issues such as heading drift, visual recognition deviation, accumulated ranging errors, and inconsistent control responses during actual operations.

[0005] Therefore, it is necessary to provide a multi-sensor rapid calibration solution for industrial UAVs in the final assembly state, so that the UAV can complete multi-attitude sampling, unified orientation benchmark verification, vision and ranging joint calibration, automatic parameter solution and write-back, and result traceability in a single clamping, so as to meet the application requirements of mass manufacturing, delivery inspection and return to factory for recalibration. Summary of the Invention

[0006] To address the technical problems of low calibration efficiency, inconsistent attitude and orientation references, lack of unified coordinate references among different sensors, and insufficient consistency and traceability of calibration results in the multi-sensor calibration process after industrial drone assembly, this invention provides a method for joint multi-sensor calibration of industrial drones after assembly. The technical solution is as follows: A method for joint calibration of multiple sensors after final assembly of an industrial UAV is provided, including: Under single-clamping conditions, the industrial UAV under test is fixed to the fixed platform of the body, and the zero position of the whole machine attitude is established based on the horizontal reference module; Under the condition that the clamping state remains unchanged, the industrial UAV under test is driven to switch to multiple preset attitudes by a multi-attitude flipping mechanism, and inertial measurement unit data is collected in each preset attitude to construct an attitude error dataset. At the zero attitude position, the reference orientation of the tested industrial UAV is aligned with the standard orientation provided by the orientation reference module, and magnetic compass data and RTK orientation data are collected to construct a heading error dataset; Under the same overall coordinate reference system, the vision module and the ranging module are oriented towards the calibration target with known spatial geometric relationships to collect image data and distance data in order to construct a vision dataset and a ranging dataset. Based on the attitude error dataset, heading error dataset, vision dataset, and ranging dataset, a joint solution is performed under the constraints of a unified whole-machine coordinate system to obtain the installation deviation parameters and compensation parameters between multiple sensors. The compensation parameters are written into the flight controller and each sensor control unit, and corresponding calibration records are generated.

[0007] Optionally, under single-clamping conditions, fixing the industrial UAV under test to the fixed platform and establishing the overall attitude zero position based on the horizontal reference module includes: The landing gear or arms of the industrial drone under test are clamped and limited by an adjustable clamping seat. The longitudinal displacement of the industrial drone under test is limited by front and rear limiting structures; The center position of the industrial drone under test is aligned using a central positioning structure. The current attitude of the aircraft is detected by the horizontal reference module, and the fixed platform of the aircraft is adjusted to the horizontal zero position.

[0008] Optionally, under the condition that the clamping state remains unchanged, the step of driving the industrial UAV under test to switch to multiple preset attitudes through a multi-attitude flipping mechanism, and collecting inertial measurement unit data in each preset attitude, includes: The multi-attitude flipping mechanism is controlled to make the industrial UAV under test sequentially occupy at least two of the following attitudes: positive pitch angle, negative pitch angle, positive roll angle, and negative roll angle. After each preset attitude is reached, the inertial measurement unit is triggered to collect data through the attitude confirmation signal. The acceleration data and angular velocity data under each attitude are combined to form an attitude error dataset.

[0009] Optionally, in the zero-attitude position, aligning the reference orientation of the tested industrial UAV with the standard orientation provided by the orientation reference module, and acquiring magnetic compass data and RTK orientation data, includes: A baseline is projected onto the reference plane using a laser alignment device; Adjust the centerline of the industrial UAV under test to coincide with the baseline; Magnetic compass data and RTK orientation data were acquired at at least one yaw scale position; A heading error dataset is constructed based on the difference between the reference direction and the measurement direction.

[0010] Optionally, the acquisition of image data and distance data, under the same overall coordinate reference system, involves oriented the vision module and the ranging module towards a calibration target with known spatial geometric relationships, including: The camera acquires images of a chessboard calibration board using a vision module to obtain in-camera distortion parameters. The camera extrinsic deviation is obtained by acquiring images of a vertical reference board through a vision module. The ranging module measures the target at close range, medium range, and long range to obtain multiple distance data points. The multiple distance target plates are arranged along the same reference axis.

[0011] Optionally, based on the attitude error dataset, heading error dataset, vision dataset, and ranging dataset, a joint solution is performed under the constraints of a unified whole-machine coordinate system to obtain the installation deviation parameters and compensation parameters between multiple sensors, including: Establish error models of the inertial measurement unit, magnetic compass, RTK orientation module, vision module, and ranging module relative to the overall coordinate system; Based on the aforementioned error model, coupled calculations are performed on the attitude error dataset, heading error dataset, visual dataset, and ranging dataset. Output the installation deviation parameters and compensation parameters for each sensor.

[0012] Optionally, the step of writing the compensation parameters into the flight controller and each sensor control unit, and generating corresponding calibration records, includes: Write the inertial measurement unit parameters into the flight control system; Write the heading compensation parameters into the navigation module; Write the visual parameters into the visual processing module; Write the ranging compensation parameters into the ranging module; Generate calibration records corresponding to device identifiers, time information, and calibration parameters.

[0013] On the other hand, a multi-sensor calibration fixture is provided after the final assembly of an industrial drone, applicable to the aforementioned multi-sensor joint calibration method for the final assembly of an industrial drone, including: Tooling base; A multi-posture flipping mechanism is provided on the tooling base; The body fixing platform is mounted on the multi-posture flipping mechanism; An orientation reference module and a vision and distance calibration module are mounted on the tooling base. The body fixing platform is used to fix the industrial UAV under test under single clamping conditions. The multi-attitude flipping mechanism is used to switch attitudes while maintaining the clamping relationship unchanged. The orientation reference module and the body fixing platform form a fixed direction reference relationship. The vision and ranging calibration module is located in the sampling direction of the body fixing platform.

[0014] Optionally, the machine body fixing platform includes an adjustable clamping seat, a limiting structure, and a center positioning structure.

[0015] Optionally, the multi-posture flipping mechanism includes a flipping shaft, a flipping frame, a bearing housing, and an indexing locking structure.

[0016] This application discloses a multi-sensor joint calibration method for industrial UAVs after final assembly, belonging to the field of industrial UAV calibration technology. This method fixes the UAV under test in a single clamping operation, utilizes a multi-attitude flipping mechanism to provide a standard attitude, and combines an orientation reference module to provide a unified heading reference. It completes the acquisition and coupled solution of multi-source data from IMU, magnetic compass, RTK, vision module, and ranging module within the same overall coordinate system, automatically generating and writing a complete set of compensation parameters, and simultaneously generating a calibration report with bound device identification. The accompanying tooling enables full sensor joint calibration to be completed in a single clamping operation. This invention improves calibration accuracy, consistency, and traceability, and is suitable for factory calibration, return-to-factory recalibration, and multi-mounted UAV adaptation for industrial UAVs, possessing promising prospects for industrial application. Attached Figure Description

[0017] Figure 1 A schematic diagram of the overall structure of a multi-sensor rapid calibration tooling for industrial drones after final assembly; Figure 2 A schematic diagram of the multi-pose rapid calibration fixture structure; Figure 3 A schematic diagram of a scenario for joint calibration of vision / range / azimuth. Figure 4 Flowchart of a method for rapid calibration and parameter write-back of multiple sensors; Figure 5 This is an illustration of the correspondence between the main calibration objects, output parameters, and write-back targets. Figure 6 A three-view schematic diagram for calibrating the tooling assembly and key components. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0019] In this article, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship. Example 1

[0020] A method for joint calibration of multiple sensors after final assembly of an industrial drone includes the following steps: Step S1: Under single clamping conditions, the industrial UAV under test is fixed to the fixed platform of the body, and the zero position of the whole machine attitude is established based on the horizontal reference module.

[0021] Among them, single clamping means that the UAV is not disassembled, moved or clamped again from the start of calibration to the end of the entire process, so as to avoid position offset and attitude error caused by repeated clamping.

[0022] The fixed platform establishes a stable and repeatable relative positional relationship between the UAV and the tooling through adjustable clamping, limiting and center positioning structures.

[0023] The horizontal reference module includes a high-precision level and a zero-position sensor, which are used to confirm that the tooling body and the UAV meet the horizontal reference state required for calibration. This serves as the unified attitude origin for all calibration steps, ensuring that subsequent inertial measurement unit, heading, vision and ranging data are all based on the same initial reference.

[0024] Step S2: Under the condition that the clamping state remains unchanged, the industrial UAV under test is driven to switch to multiple preset attitudes through the multi-attitude flipping mechanism, and inertial measurement unit data is collected in each preset attitude to construct an attitude error dataset.

[0025] The multi-attitude flipping mechanism drives the entire machine into standard attitudes such as positive pitch, negative pitch, positive roll, and negative roll while maintaining the clamping relationship. After each attitude is reached and stabilized, the attitude confirmation sensor triggers sampling to collect the acceleration and angular velocity outputs of the inertial measurement unit, forming a combination of raw data under multiple attitudes.

[0026] By using multi-attitude data, the zero bias, scaling factor, and installation angle error of the inertial measurement unit can be completely calculated, thereby constructing an attitude error dataset.

[0027] Step S3: With the attitude at zero position, align the reference direction of the tested industrial UAV with the preset standard orientation provided by the orientation reference module, and collect magnetic compass data and RTK orientation data to construct a heading error dataset.

[0028] The orientation reference module provides a fixed baseline or a preset standard orientation reference. The longitudinal axis of the UAV body is strictly aligned with this reference, so that the geometric direction of the UAV body, the magnetic compass measurement direction, and the RTK orientation direction share a unified orientation reference.

[0029] By comparing the baseline true value with the measured heading value, the deviation is calculated and a heading error dataset is formed for subsequent heading compensation.

[0030] Step S4: Under the same whole-machine coordinate reference system, make the vision module and the ranging module face the calibration target with known spatial geometric relationship, and collect image data and distance data to construct the vision dataset and the ranging dataset.

[0031] All calibration targets are located within a unified overall coordinate system, and their distance, size, and angle relationships are known.

[0032] The vision module acquires images of checkerboard and vertical plane targets to calculate intrinsic parameters, distortion, and extrinsic parameter deviations; the ranging module measures near, medium, and far-range targets to obtain multi-distance measured data and form a ranging dataset.

[0033] Step S5: Based on the attitude error dataset, heading error dataset, vision dataset, and ranging dataset, perform a joint solution under the constraints of a unified whole-machine coordinate system to obtain the installation deviation parameters and compensation parameters between multiple sensors.

[0034] In this process, attitude error, heading error, vision error, and ranging error are incorporated into the same whole-machine coordinate model for coupled calculation. Error models of each sensor relative to the reference point or reference plane of the whole-machine coordinate system are established. Through outlier removal, fitting calculation, and comprehensive solution, a complete set of compensation parameters for the inertial measurement unit, magnetic compass, RTK, vision, and ranging are obtained.

[0035] Step S6: Write the compensation parameters into the flight controller and each sensor control unit respectively, and generate the corresponding calibration record.

[0036] The compensation parameters are automatically written to the module partitions. Inertial measurement unit parameters are written to the flight control and inertial navigation area, heading parameters are written to the navigation fusion area, visual parameters are written to the vision controller, and ranging parameters are written to the ranging module. Simultaneously, a calibration report is generated, binding the device identifier, time information, tooling number, operator, parameter version, and template version, enabling the calibration process to be stored, queried, and traceable.

[0037] In some implementations, this method is also applicable to recalibration scenarios following factory return for re-inspection, collision repair, rack replacement, or replacement of a single sensor module. The system can retrieve historical calibration records and compare them with the current sampling results. When the difference is less than a preset threshold, a local parameter write-back is performed; when the difference is greater than the preset threshold, a complete joint calibration process is executed.

[0038] Figure 4 The flowchart of the multi-sensor rapid calibration and parameter write-back method illustrates the calibration process of this invention, including: S1. Overall machine clamping and tooling zero-position confirmation; S2. Reading the model / module configuration and loading the corresponding calibration template; S3. Multi-attitude flip sampling to acquire raw IMU data; S4. Azimuth reference calibration to calculate magnetic compass / RTK direction deviation; S5. Visual and ranging calibration to form an external participation distance compensation table; S6. Outlier removal and comprehensive calculation of compensation parameters; S7. Parameter writing to the flight controller and each sensor controller; S8. Generating and archiving a calibration report with a bound serial number. The core of this process is to complete joint sampling, automatic parameter calculation, automatic write-back, and automatic record keeping under unified clamping, unified reference, and unified template, reducing reliance on manual experience and improving batch consistency.

[0039] This embodiment achieves one-stop joint calibration of multiple sensors after the final assembly of an industrial UAV through single clamping, multi-stage unified benchmark acquisition, and coupled solution of the whole machine coordinate system. It fundamentally solves the problems of cumbersome traditional manual calibration process, poor attitude repeatability, inconsistent benchmarks, reliance on experience, and lack of traceability system. It significantly improves calibration accuracy, consistency, and industrial batch adaptability. At the same time, it is compatible with multiple usage scenarios such as factory calibration, platform adaptation, and return to factory for recalibration, effectively improving the overall assembly quality, flight control stability, and operational reliability. Example 2

[0040] Based on Example 1, further for step S1, under single clamping conditions, the industrial UAV under test is fixed to the body fixing platform and the zero position of the whole machine attitude is established based on the horizontal reference module. Specifically, this includes: clamping and limiting the landing gear or arm of the industrial UAV under test through the adjustable clamping seat; limiting the longitudinal displacement of the industrial UAV under test through the front and rear limiting structures; aligning the center position of the industrial UAV under test through the center positioning structure; detecting the current attitude of the body based on the horizontal reference module, and adjusting the body fixing platform to meet the horizontal reference state required for calibration.

[0041] The adjustable clamping seat features a left-right sliding structure with continuously adjustable spacing, positional positioning, or switching via an array of positioning holes to adapt to different wheelbases, landing gear widths, or arm outer edge dimensions. The clamping contact surface is equipped with elastic pads and wear-resistant blocks, employing a multi-point support method to prevent excessive local stress from causing frame deformation, while ensuring stable clamping without slippage. Front and rear limiting structures restrict the UAV's movement along its fuselage length, ensuring consistent longitudinal positioning. The center positioning structure aligns with the UAV's belly center plate, dedicated positioning holes, or structural reference surfaces, aligning the overall geometric center of the aircraft with the tooling center, improving clamping repeatability and positioning accuracy.

[0042] In some implementations, the mounting platform may also be provided with a clearance structure in the belly area to avoid the mounting brackets or bases of cleaning, hoisting and other types of machines.

[0043] This embodiment achieves rapid, stable, stress-free, and repeatable clamping of UAVs through a combination of multi-level limiting, adjustable clamping, center alignment, and horizontal confirmation. It effectively avoids clamping deformation, positioning deviation, and attitude shift, while being compatible with multiple UAV structures and mounting layouts. This provides a reliable foundation for high-precision calibration and improves the versatility and adaptability of the tooling. Example 3

[0044] Based on Example 1, further for step S2, under the condition that the clamping state remains unchanged, the industrial UAV under test is driven to switch to multiple preset attitudes and collect inertial measurement unit data through a multi-attitude flipping mechanism. Specifically, this includes: controlling the multi-attitude flipping mechanism to make the industrial UAV under test sequentially occupy at least two attitudes among positive pitch angle, negative pitch angle, positive roll angle, and negative roll angle; after each preset attitude is in place, the inertial measurement unit is triggered to collect data through an attitude confirmation signal; and the acceleration data and angular velocity data under each attitude are combined to form an attitude error dataset.

[0045] The multi-attitude flipping mechanism includes a roll flipping axis, a pitch flipping frame, and a yaw indexing mechanism, enabling stable, precise, and repeatable angle switching. Once the attitude is in position, the attitude confirmation sensor outputs a lock signal, and the system only starts data acquisition from the inertial measurement unit after the attitude has stabilized, avoiding noise interference from sampling during motion. In a preferred embodiment, data on positive pitch angles, negative pitch angles, positive roll angles, and negative roll angles are collected sequentially, and combined with zero-position data for comprehensive calculation when necessary.

[0046] This embodiment uses mechanically standardized attitude to replace manual positioning, resulting in high attitude repeatability and strong stability. It significantly reduces calibration deviations caused by human factors, improves the calibration accuracy and consistency of the inertial measurement unit, and makes flight control attitude calculation more stable and reliable. It is especially suitable for high-precision calibration scenarios of heavy-load and large-size industrial UAVs. Example 4

[0047] Based on Example 1, step S3 is further improved by aligning the reference direction of the tested industrial UAV with the preset standard orientation provided by the orientation reference module at the zero attitude position and collecting magnetic compass and RTK orientation data. Specifically, this includes: projecting a reference line onto the reference plane using a laser alignment device; adjusting the center line of the tested industrial UAV to coincide with the reference line; collecting magnetic compass data and RTK orientation data at at least one yaw scale position; and constructing a heading error dataset based on the difference between the reference direction and the measurement direction.

[0048] The laser alignment device projects a high-alignment baseline, providing a non-contact, high-precision, and visual orientation reference. Once the aircraft's centerline coincides with the baseline, the zero-position of the aircraft's longitudinal axis orientation is established. The yaw indexing mechanism provides fixed angle increments, supports multi-point heading sampling, and improves the robustness of heading calculations. The orientation reference module may further include a graduated scale structure, the main body of which or adjacent support components are preferably made of low-permeability materials and are arranged in an isolated layout to reduce disturbances to magnetic measurements from the calibration environment.

[0049] Figure 3 This is a schematic diagram of a vision / range / azimuth joint calibration scenario. The diagram includes: a tooling unit and the UAV under test (equipped with a camera / ToF / laser rangefinder module), a near-range target area (1m checkerboard reference board), a mid-range target area (3m checkerboard + grayscale reference board), a far-range target area (5m reflector reference board), and an azimuth baseline / laser aligner / fixed orientation reference at the top. The UAV's sensing axis is aligned sequentially with the near-range, mid-range, and far-range target areas, forming a calibration scene arranged along the same axis.

[0050] The UAV completes the following in sequence under the same clamping condition: camera intrinsic and extrinsic parameter calibration, ranging deviation calibration, and consistency calibration of the aircraft's longitudinal axis and heading reference line.

[0051] Figure 3 The camera / ToF / laser ranging module's measurement axis is designed to be collinear with the near / medium / far-range target plates (1m, 3m, 5m), and its center height is aligned with the sensor's optical axis. This design ensures that the vision module and the ranging module complete data acquisition under the same posture, orientation, and reference, eliminating systematic errors caused by repeated clamping or posture deviation.

[0052] The checkerboard pattern at close range (1m) in the figure is mainly used for camera intrinsic parameter calibration, solving basic parameters such as distortion and focal length, and can also be used for close-range ranging data sampling.

[0053] The image shows a 3m mid-range checkerboard pattern and a grayscale plate: the checkerboard pattern is used for camera extrinsic parameters and installation angle calibration; the grayscale plate (reflectivity reference plate) is used to correct image brightness response and recognition threshold, while also providing mid-range ranging data points.

[0054] The long-distance (5m) reflector in the diagram is used to collect long-distance ranging data, correct the proportional deviation and nonlinear error of the ranging module, and form a complete distance compensation table.

[0055] The azimuth reference line / laser aligner at the top of the diagram unifies the orientation and heading references, providing a unified reference for the UAV's longitudinal axis, magnetic compass, and RTK orientation module. By aligning the UAV's centerline with the reference line, the references for the UAV's geometric direction, magnetic measurement direction, and RTK orientation direction are unified, solving the problems of ambiguous heading references and inconsistent headings among multiple systems in traditional calibration.

[0056] The scene shown in the image is reused, and the drone remains stationary throughout the entire calibration process, from setup to completion. Calibration of the camera, rangefinder, and heading sensors is completed in a single step by facing different target areas. This significantly improves calibration efficiency while avoiding positioning errors caused by multiple setups, ensuring that all sensor data are based on the same overall drone coordinate system.

[0057] This embodiment provides a unified orientation reference for the aircraft, magnetic compass, and RTK, solving the problems of ambiguous headings and inconsistent headings among multiple systems in traditional calibration. It significantly improves the overall heading stability and orientation accuracy of the aircraft, while reducing environmental magnetic field interference and improving navigation reliability under complex operating conditions. Example 5

[0058] Based on Example 1, step S4 is further improved by having the vision module and the ranging module face the calibration target with known spatial geometric relationships and acquire images and distance data under the same whole-machine coordinate reference system. Specifically, this includes: acquiring images of the checkerboard calibration board through the vision module to obtain camera intrinsic distortion parameters; acquiring images of the vertical reference board through the vision module to obtain camera extrinsic deviation; measuring the near-range target board, the medium-range target board, and the far-range target board through the ranging module to obtain multiple distance data points; and arranging multiple distance target boards along the same reference axis.

[0059] The checkerboard calibration plate is used to calculate camera intrinsic parameters, radial distortion, and tangential distortion; the vertical plane reference plate is used to determine the installation extrinsic parameters of the camera optical axis relative to the overall coordinate system; the near-range, medium-range, and far-range target plates are arranged along the same straight line, with their center height aligned with the center of the UAV sensor optical axis to reduce measurement deviations introduced by the pitch angle. In some embodiments, grayscale or reflectivity reference plates can also be set to correct the image brightness response or recognition threshold of the vision module.

[0060] like Figure 2 As shown, the diagram includes an azimuth baseline, laser alignment device, fixed orientation reference, long-range target area, medium-range target area, short-range target area, checkerboard calibration board, checkerboard + grayscale board, reflector, camera / ToF, 1m / 3m / 5m reference boards, laser ranging module, tooling, and the UAV under test. The diagram illustrates the UAV performing camera intrinsic and extrinsic parameter calibration, ranging deviation calibration, and alignment of the aircraft's longitudinal axis with the heading reference line in the same clamping configuration.

[0061] Figure 2 This invention embodies the core design principles of unified overall coordinates, single-clamping, and simultaneous calibration of multiple sensors. By arranging near / medium / far-range targets along the same axis, the vision module and ranging module complete data acquisition under the same posture, orientation, and reference, eliminating systematic errors caused by repeated clamping and posture deviation. The grayscale plate, reflector, and vertical reference plate enable simultaneous camera brightness correction, distortion correction, extrinsic parameter correction, and ranging compensation, achieving joint calibration of vision and ranging.

[0062] This embodiment achieves synchronous calibration of vision and ranging under a unified coordinate system. The camera's intrinsic and extrinsic parameters, ranging compensation curve, and overall coordinate system are strictly aligned, significantly improving the accuracy of visual positioning and the stability of close-range ranging. It is particularly suitable for operation scenarios with stringent requirements for perception accuracy, such as near-wall cleaning, precision hoisting, and close-range inspection. Example 6

[0063] Based on Example 1, step S5 is further improved by performing joint solution based on multiple datasets under the constraints of a unified whole-machine coordinate system to obtain the installation deviation parameters and compensation parameters of multiple sensors. Specifically, this includes: establishing error models of the inertial measurement unit, magnetic compass, RTK orientation module, vision module, and ranging module relative to the reference point or reference plane of the whole-machine coordinate system; performing coupled calculations on the attitude error dataset, heading error dataset, vision dataset, and ranging dataset based on the error models; and outputting the installation deviation parameters and compensation parameters of each sensor.

[0064] Among them, the unified whole coordinate system serves as a common reference benchmark, mapping the errors of each sensor to the same space; the error model includes core items such as installation offset angle, zero offset, scaling factor, distance deviation, and coordinate transformation matrix; coupled calculation constrains the multi-source data and solves iteratively to eliminate the coordinate mapping error caused by decentralized calibration, and finally outputs a complete compensation parameter package.

[0065] like Figure 5 As shown in the table, which lists the main calibration objects, output parameters, and write-back targets, the calibration logic of each sensor in this invention is clearly defined. The IMU (Inertial Measurement Unit) samples through multi-attitude flipping, outputting zero bias, proportional coefficient, and installation error, which are then written into the flight control / inertial navigation parameter area. The magnetic compass / RTK samples through a fixed orientation baseline and graduation position, outputting heading compensation and direction consistency parameters, which are then written into the heading fusion or navigation parameter area. The vision module samples through a checkerboard / vertical reference board, outputting intrinsic parameters, distortion, and extrinsic parameter deviations, which are then written into the vision controller configuration file. The ranging module samples through near, medium, and long-range reference targets, outputting a distance compensation table and installation angle correction, which are then written into the ranging module parameter area. This table clearly demonstrates the division of labor and parameter management logic for multi-sensor joint calibration.

[0066] This embodiment achieves unified correction of system errors at the whole-machine level through multi-sensor coupling solution, which greatly improves the fusion accuracy of flight control, navigation and perception systems, ensures the stability of flight control and close-range operations, and makes multi-sensor data consistent at the whole-machine level, avoiding problems such as positioning drift and attitude jitter caused by inconsistent coordinates. Example 7

[0067] Based on Example 1, step S6 is further improved by writing the compensation parameters into the flight control system and each sensor control unit and generating corresponding calibration records. Specifically, this includes: writing the inertial measurement unit parameters into the flight control system; writing the heading compensation parameters into the navigation module; writing the visual parameters into the visual processing module; writing the ranging compensation parameters into the ranging module; and generating calibration records corresponding to the equipment identifier, time information, tooling number, operator, parameter version, template version, and calibration results.

[0068] The parameters are automatically written according to the functional partitions, eliminating the need for manual configuration and reducing operational errors. The calibration record includes the UAV serial number, model information, calibration time, tooling number, operator, parameter version, template version, and calibration results, which can be used for factory quality inspection, return inspection, after-sales analysis, and quality traceability.

[0069] This embodiment achieves automatic parameter write-back and full calibration traceability, establishing a complete quality closed loop from manufacturing to delivery to after-sales service, improving the efficiency and manageability of industrialized batch delivery, and providing data support for equipment lifecycle quality traceability, fault analysis, and process optimization, thereby improving product standardization and maintainability. Example 8

[0070] A multi-sensor calibration fixture for industrial UAVs after final assembly, applicable to any of the methods in Examples 1 to 7, includes a fixture base, a multi-attitude flipping mechanism disposed on the fixture base, a body fixing platform mounted on the multi-attitude flipping mechanism, an orientation reference module and a vision and ranging calibration module disposed on the fixture base.

[0071] The system comprises a fixed mounting platform for securing the industrial UAV under test in a single clamping operation; a multi-attitude flipping mechanism for switching attitudes while maintaining the clamping relationship; a fixed directional reference relationship between the orientation reference module and the fixed mounting platform; and a vision and ranging calibration module located on the sampling direction of the fixed mounting platform. Each module establishes a fixed positional relationship relative to the tooling base and collectively serves the establishment and joint calibration of a unified overall coordinate system.

[0072] This embodiment provides an integrated calibration fixture with a compact structure, unified benchmark, and complete functions. It supports joint calibration of all sensors in a single clamping, and is suitable for batch calibration on the production line, rapid on-site recalibration, and calibration for return to the factory for maintenance, which greatly improves the efficiency and consistency of industrial UAV assembly and calibration.

[0073] Based on Embodiment 8, the fuselage fixing platform includes left and right adjustable clamping seats, front and rear limit blocks, landing gear locking parts and center positioning structure.

[0074] The adjustable left and right clamping seats are designed to accommodate landing gear or booms of different widths; the front and rear limiting blocks restrict the longitudinal displacement of the UAV; the landing gear locking mechanism provides positioning and support for the landing gear; and the center positioning structure ensures precise alignment between the entire aircraft and the tooling center. The clamping surfaces utilize elastic padding to prevent stress deformation of the frame.

[0075] Through a multi-level positioning structure, it achieves fast clamping, accurate positioning, and strong compatibility, and can be adapted to multiple models and platforms of industrial drones, improving the versatility and repeatability of tooling and reducing the impact of clamping errors on calibration results.

[0076] Based on Embodiment 8, the multi-posture flipping mechanism includes a flipping shaft, a flipping frame, a bearing housing, and an indexing locking structure. The flipping shaft and bearing housing ensure smooth rotation and minimal clearance; the flipping frame provides high rigidity; the indexing locking structure uses positioning pins, an indexing plate, or a servo drive to achieve precise locking of standard angles, ensuring repeatability of the posture. In some embodiments, the multi-posture flipping mechanism also includes a posture confirmation sensor for outputting a posture positioning signal.

[0077] Figure 1 This diagram illustrates the overall structure of a multi-sensor rapid calibration fixture for an industrial drone after assembly. It showcases the system's architecture, comprising three parts: the industrial drone to be calibrated, the main body of the integrated calibration fixture, and peripheral modules. The industrial drone to be calibrated uses the fuselage center plate, flight control / power / positioning module, landing gear, or arm fixed points as positioning references. The main body of the integrated calibration fixture consists of a fixed base / horizontal reference platform, a multi-attitude flipping frame, and a fuselage clamping mechanism, supporting standard attitude switching of pitch, roll, and yaw. The peripheral modules include an azimuth reference module, a vision / range measurement target module, and a data acquisition and writing terminal, collectively enabling multi-sensor joint calibration and parameter management.

[0078] Figure 2 This diagram illustrates the structure of a multi-attitude rapid calibration fixture, showcasing its core mechanical components, including: ① an adjustable landing gear holder, ② a roll bearing and drive mechanism, ③ a fixture level / zero-position sensor, ④ a pitch-flipping frame, ⑤ a yaw positioning indexing dial, ⑥ cable adapters and data interfaces, and the central mounting area for the UAV under test. Through its standard zero-position, multi-axis flipping, and repeatable positioning design, this fixture enables the IMU, magnetic compass, RTK orientation, vision module, and ranging module to complete joint calibration in a single clamping configuration.

[0079] Figure 6 This document provides a three-view diagram of the tooling assembly and key components, including the assembly three-view sheet, the rotating frame, the clamping platform, and the target / reference frame. The overall dimensions of the tooling assembly are 1600mm × 600mm. Each view clearly shows the spatial relationship between the tooling base, the flipping mechanism, the clamping platform, and the target frame. The individual views of the rotating frame, clamping platform, and target frame further clarify the structural details and assembly datum of each component, providing intuitive support for the mechanical design and implementation of the tooling.

[0080] This embodiment achieves stable, accurate, and repeatable multi-attitude switching, replacing manual handling, significantly improving calibration efficiency and safety, while ensuring attitude angle accuracy and improving the consistency and reliability of inertial measurement unit and heading calibration.

[0081] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0082] The above description is merely an optional embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. An industrial unmanned aerial vehicle post-assembly multi-sensor joint calibration method, characterized in that, include: Under single-clamping conditions, the industrial UAV under test is fixed to the fixed platform of the body, and the zero position of the whole machine attitude is established based on the horizontal reference module; Under the condition that the clamping state remains unchanged, the industrial UAV under test is driven to switch to multiple preset attitudes by a multi-attitude flipping mechanism, and inertial measurement unit data is collected in each preset attitude to construct an attitude error dataset. At the zero attitude position, the reference orientation of the tested industrial UAV is aligned with the standard orientation provided by the orientation reference module, and magnetic compass data and RTK orientation data are collected to construct a heading error dataset; Under the same overall coordinate reference system, the vision module and the ranging module are oriented towards the calibration target with known spatial geometric relationships to collect image data and distance data in order to construct a vision dataset and a ranging dataset. Based on the attitude error dataset, heading error dataset, vision dataset, and ranging dataset, a joint solution is performed under the constraints of a unified whole-machine coordinate system to obtain the installation deviation parameters and compensation parameters between multiple sensors. The compensation parameters are written into the flight controller and each sensor control unit, and corresponding calibration records are generated.

2. The method of claim 1, wherein, Under single-clamping conditions, the industrial UAV under test is fixed to the fixed platform of the aircraft body, and the zero position of the whole attitude is established based on the horizontal reference module, including: The landing gear or arms of the industrial drone under test are clamped and limited by an adjustable clamping seat. The longitudinal displacement of the industrial drone under test is limited by front and rear limiting structures; The center position of the industrial drone under test is aligned using a central positioning structure. The current attitude of the aircraft is detected by the horizontal reference module, and the fixed platform of the aircraft is adjusted to the horizontal zero position.

3. The method of claim 1, wherein, Under the condition that the clamping state remains unchanged, the industrial UAV under test is driven to switch to multiple preset attitudes through a multi-attitude flipping mechanism, and inertial measurement unit data is collected in each preset attitude, including: The multi-attitude flipping mechanism is controlled to make the industrial UAV under test sequentially occupy at least two of the following attitudes: positive pitch angle, negative pitch angle, positive roll angle, and negative roll angle. After each preset attitude is reached, the inertial measurement unit is triggered to collect data through the attitude confirmation signal. The acceleration data and angular velocity data under each attitude are combined to form an attitude error dataset.

4. The method of claim 1, wherein, In the zero-attitude position, the reference orientation of the tested industrial UAV is aligned with the standard orientation provided by the orientation reference module, and magnetic compass data and RTK orientation data are collected, including: A baseline is projected onto the reference plane using a laser alignment device; Adjust the centerline of the industrial UAV under test to coincide with the baseline; Magnetic compass data and RTK orientation data were acquired at at least one yaw scale position; A heading error dataset is constructed based on the difference between the reference direction and the measurement direction.

5. The method of claim 1, wherein, The acquisition process involves using the same overall coordinate reference system, with the vision module and ranging module facing a calibration target having known spatial geometric relationships, to acquire image data and distance data, including: The camera acquires images of a chessboard calibration board using a vision module to obtain in-camera distortion parameters. The camera extrinsic deviation is obtained by acquiring images of a vertical reference board through a vision module. The ranging module measures the target at close range, medium range, and long range to obtain multiple distance data points. The multiple distance target plates are arranged along the same reference axis.

6. The method of claim 1, wherein, Based on the attitude error dataset, heading error dataset, vision dataset, and ranging dataset, a joint solution is performed under the constraints of a unified whole-machine coordinate system to obtain the installation deviation parameters and compensation parameters between multiple sensors, including: Establish error models of the inertial measurement unit, magnetic compass, RTK orientation module, vision module, and ranging module relative to the overall coordinate system; Based on the aforementioned error model, coupled calculations are performed on the attitude error dataset, heading error dataset, visual dataset, and ranging dataset. Output the installation deviation parameters and compensation parameters for each sensor.

7. The method of claim 1, wherein, The step of writing the compensation parameters into the flight controller and each sensor control unit, and generating corresponding calibration records, includes: Write the inertial measurement unit parameters into the flight control system; Write the heading compensation parameters into the navigation module; Write the visual parameters into the visual processing module; Write the ranging compensation parameters into the ranging module; Generate calibration records corresponding to device identifiers, time information, and calibration parameters.

8. An industrial unmanned aerial vehicle post-assembly multi-sensor calibration tool, characterized in that, The multi-sensor joint calibration method applicable to the industrial UAV after final assembly as described in any one of claims 1 to 7 includes: Tooling base; A multi-posture flipping mechanism is provided on the tooling base; The body fixing platform is mounted on the multi-posture flipping mechanism; An orientation reference module and a vision and distance calibration module are mounted on the tooling base. The body fixing platform is used to fix the industrial UAV under test under single clamping conditions. The multi-attitude flipping mechanism is used to switch attitudes while maintaining the clamping relationship unchanged. The orientation reference module and the body fixing platform form a fixed direction reference relationship. The vision and ranging calibration module is located in the sampling direction of the body fixing platform.

9. The tooling of claim 8, wherein, The machine body fixing platform includes an adjustable clamping seat, a limiting structure, and a center positioning structure.

10. The tooling according to claim 8, characterized in that, The multi-posture flipping mechanism includes a flipping shaft, a flipping frame, a bearing housing, and an indexing locking structure.

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