Sensor Calibration Optimization with Loop Constraints for Fusion Accuracy
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Solution Overview
Problem
Existing sensor calibration methods in autonomous vehicles and robotics applications suffer from minute errors that affect the accuracy of sensor fusion, necessitating high-accuracy calibration for improved perception models.
Innovation Solution
A method and system for optimizing sensor calibration using extrinsic and temporal calibration parameters, applying loop constraints to minimize errors through least-squares minimization and the Levenberg Marquardt algorithm, specifically for extrinsic calibrations involving rigid transformations and temporal calibrations based on timestamp differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are calibrated using conventional methods, then calibration can be completed with predetermined vector size, but minute errors accumulate affecting sensor fusion accuracy
Solution Approach 1:
The patent applies loop constraints that modify calibration parameters to satisfy closure equations. The optimization process changes the calibration parameters iteratively using the Levenberg-Marquardt algorithm to minimize errors while maintaining the loop constraint, thereby improving both measurement precision and reliability of sensor fusion
Solution Approach 2:
The patent implements a feedback mechanism where the loop constraint error is calculated and fed back into the optimization process. The minimization function uses this feedback to adjust calibration parameters, continuously improving accuracy until the loop constraint is satisfied within acceptable tolerances
2Measurement precision
If calibration optimization with loop constraints is applied, then calibration errors are reduced by up to 1/n, but computational complexity increases
Solution Approach 1:
The patent applies partial optimization by focusing computational effort on satisfying the loop constraint rather than optimizing all calibration parameters independently. This selective approach reduces the overall computational burden while achieving the critical error reduction needed for accurate sensor fusion
3Measurement precision
If extrinsic and temporal calibration parameters are optimized together, then overall calibration accuracy improves, but the calibration process becomes more complex
Solution Approach 1:
The patent merges extrinsic calibration parameters (spatial relationships) and temporal calibration parameters (timestamp synchronization) into a unified optimization framework. By combining these calibration types and applying loop constraints to the integrated system, the patent achieves improved overall accuracy while managing complexity through a cohesive mathematical formulation
Data Source
AI summary
A system and method for calibration optimization. The system includes a plurality of sensors, a processing circuitry and a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system to receive a signal from a plurality of sensors, perform a calibration on the plurality of sensors, the calibration having a predetermined vector size corresponding to a plurality of parameters of the calibrations, and perform an optimization after the calibration. The optimization includes a minimization that includes applying a loop constraint.