Inertial Navigation System Delta Position and Attitude Aiding
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Solution Overview
Problem
Inertial navigation systems face challenges in maintaining accuracy due to integration drift and error growth, especially in GNSS denied environments where external aiding is limited, and they struggle to handle aggressive motion and featureless environments effectively.
Innovation Solution
The integration of an inertial navigation system with external aiding sensors and imaging sensors like cameras and lidars, which provide delta attitude and position measurements, allows for calibration of inertial sensor errors using a computation device that processes data from these sensors to reduce error growth and improve navigation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If inertial navigation system operates independently without external aiding, then system complexity is reduced, but navigation accuracy deteriorates due to integration drift and error growth
Solution Approach 1:
The patent introduces external aiding systems (visual odometry, lidar odometry, GNSS) as intermediary components that provide corrective measurements to the inertial navigation system. These external systems act as mediators that supply position and attitude information to calibrate and correct the drift errors in the inertial sensors, thereby improving navigation accuracy without requiring fundamental changes to the core INS architecture
Solution Approach 2:
The patent implements feedback mechanisms where external aiding measurements are continuously fed back to the inertial navigation system to correct accumulated errors. The system uses visual odometry, lidar odometry, and GNSS measurements as feedback signals to adjust and recalibrate the inertial sensor readings, creating a closed-loop system that actively compensates for integration drift and maintains long-term navigation accuracy
2Measurement precision
If external aiding sensors are integrated to improve accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent designs the external aiding system to perform multiple functions simultaneously. The same external sensors and processing pipeline are used for both visual odometry and lidar odometry, and can also integrate GNSS when available. This multi-functional approach allows the system to improve navigation accuracy through diverse measurement sources while avoiding the complexity of separate dedicated systems for each sensing modality
Solution Approach 2:
The patent combines multiple external aiding approaches (visual odometry, lidar odometry, GNSS) into a unified navigation solution. By merging these different sensing modalities and integrating their measurements with inertial data in a cohesive framework, the system achieves improved accuracy while managing complexity through shared processing infrastructure and coordinated operation of multiple sensors
3Reliability
If traditional inertial navigation is used in GNSS denied environments, then system simplicity is maintained, but reliability deteriorates due to error growth
Solution Approach 1:
In GNSS denied environments, the patent relies on visual odometry and lidar odometry as intermediary systems to provide the corrective measurements that would normally come from GNSS. These external vision-based systems act as mediators that supply position and attitude information to correct inertial drift, maintaining navigation reliability when traditional GNSS aiding is unavailable
Solution Approach 2:
The patent implements feedback mechanisms using visual and lidar odometry measurements to continuously correct inertial navigation errors in GNSS denied environments. The system processes external visual and lidar measurements as feedback signals to adjust and recalibrate the inertial sensor readings, creating a closed-loop system that actively compensates for integration drift and maintains long-term navigation accuracy without relying on GNSS
4Measurement precision
If visual and lidar sensors are integrated for odometry, then measurement precision is improved, but ease of operation deteriorates due to processing complexity
Solution Approach 1:
The patent combines visual odometry and lidar odometry processing into a unified framework that shares common computational infrastructure. By merging the processing pipelines and integrating measurements from both modalities through a coordinated algorithmic approach, the system achieves improved odometry precision while managing processing complexity through shared resources and synchronized operation
Data Source
AI summary
Systems and methods for the external aiding of inertial navigation systems are described herein. In certain embodiments, a device includes an inertial navigation system. In some embodiments, the inertial navigation system includes one or more inertial sensors and an input interface for receiving measurements. In further embodiments, the measurements include at least one of delta attitude and/or delta position measurements from an external system, and position and attitude information in an arbitrary map frame. In certain embodiments, the inertial navigation system includes a computation device that is configured to calibrate the errors from the one or more inertial sensors using the received measurements.