IMU Mounting Alignment Calibration via Vehicle Pose Sequences
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Solution Overview
Problem
Existing calibration systems for inertial measurement units (IMUs) on construction vehicles fail to accurately account for sensor heading and mounting alignment errors, leading to misattribution of sensor readings and errors in pose sensing, especially in high-precision applications where manual alignment is inaccurate and time-consuming.
Innovation Solution
A computer program product with a partially automated calibration routine that involves a sequence of poses for the construction vehicle, including alignments in opposite directions and positions, to determine and update IMU mounting alignments using acceleration values from multiple IMUs, eliminating the need for manual assumptions and measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual alignment and assumption of perfect alignment is used for IMU mounting, then the calibration process is simple, but the measurement precision and manufacturing precision deteriorate due to misalignment errors
Solution Approach 1:
The calibration system uses the IMU sensors themselves to automatically detect and quantify mounting alignment errors. The system self-calibrates by having the vehicle assume a sequence of known poses and using the sensor readings to compute misalignment parameters without external alignment tools or manual measurements.
Solution Approach 2:
The system changes the operational parameters of the vehicle by moving it through a defined sequence of poses (different positions and orientations) to collect calibration data. By varying the vehicle's spatial configuration, the system can solve for multiple alignment parameters including heading, roll, and pitch misalignments.
2Device complexity
If manual alignment measurement is used for IMU mounting, then the device complexity is low, but the measurement precision and time consumption worsen due to difficulty in accurately measuring alignments on large machine components
Solution Approach 1:
The system replaces manual mechanical alignment measurement tools (levels, protractors, rulers) with an automated sensor-based computational system. The IMU sensors and processing algorithm substitute for human operators physically measuring and calculating alignment parameters on large machine components.
Solution Approach 2:
The calibration algorithm acts as an intermediary that translates raw IMU sensor readings taken during known vehicle poses into corrected alignment parameters. This computational intermediary bridges the gap between sensor data and accurate alignment characterization without requiring direct physical measurement of the mounting surfaces.
3Measurement precision
If automated calibration routine with sequence of poses is implemented, then the measurement precision and productivity improve, but the device complexity and ease of operation worsen due to multiple required vehicle positions
Solution Approach 1:
The system uses feedback from the IMU sensors during each pose to automatically compute the alignment parameters. The calibration routine continuously monitors sensor readings and uses them to solve for misalignment parameters, providing automatic feedback that eliminates the need for manual measurement and calculation at each step.
Solution Approach 2:
The calibration system requires preliminary definition of the vehicle's pose sequence and the relationship between sensor coordinates and vehicle coordinates. This preliminary setup includes specifying the expected positions and orientations, which then enables automatic computation of alignment errors from the actual sensor readings during calibration.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution provides accurate and efficient calibration of IMU mounting alignments, reducing the need for manual recalibration checks and ensuring precise sensor data, even in complex vehicle configurations like dozers with 6-way blades, by automatically identifying and correcting misalignments.
Implementation Method 1
the N calibration measurements comprise at least acceleration values of acceleration sensors of the set of IMUs
Data Source
AI summary
A computer program product comprising a program code, wherein the program code is configured for calibrating mounting alignments of a set of inertial measurement units (IMUs) on a construction vehicle, wherein the set of IMUs comprises at least two IMUs each being mounted on different parts of the construction vehicle, and provides an at least partially automatically executing calibration routine for the mounting alignments of the set of IMUs on the construction vehicle, wherein for the calibration routine the following is defined: a sequence of N calibration measurements, with N greater than or equal to three, is to be carried out by the set of IMUs, and for each I-th of the N calibration measurements, with I consecutively from one to N, an I-th pose of the construction vehicle is to be adopted.