Autonomous Navigation Calibration Map for Sensor Drift Correction
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Solution Overview
Problem
Autonomous navigation systems face challenges with signal obstructions and sensor drift, leading to unbounded errors in heading estimation, particularly when GNSS signals are unavailable due to obstructions like buildings and trees.
Innovation Solution
A calibration system for autonomous navigation vehicles that generates a calibration map with overall calibration index values, determining suitable locations for calibration based on GNSS availability and path reliability, using a combination of sensors and image analysis to assess obstructions and environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GNSS signals are used for navigation, then positioning accuracy is improved, but signal availability deteriorates due to obstructions like buildings and trees
Solution Approach 1:
The system performs preliminary calibration operations at designated calibration map locations before normal navigation begins. These locations are pre-identified as having good GNSS signal availability, allowing the system to establish accurate baseline sensor readings before entering obstructed areas where GNSS signals may be lost.
Solution Approach 2:
The calibration map serves as an intermediary structure that mediates between GNSS-dependent positioning and sensor-based navigation. By storing calibration data at specific locations with known good signal availability, the system can switch between GNSS and sensor-based modes smoothly, using the calibration map as a reference for when and where to perform calibration operations.
2Duration of action of stationary object
If sensor-based navigation is used to compensate for GNSS unavailability, then navigation continuity is improved, but heading estimation accuracy deteriorates due to gyroscope drift
Solution Approach 1:
The system performs periodic calibration operations at calibration map locations during navigation. Instead of continuous calibration, the system periodically stops at predetermined locations with known good GNSS signal availability to recalibrate sensors, thereby correcting drift accumulation while maintaining navigation continuity between calibration points.
Solution Approach 2:
The calibration map provides feedback mechanisms by storing calibration data at specific locations. When the vehicle returns to or passes these locations, the system can compare current sensor readings with stored calibration data to detect drift and trigger recalibration operations, creating a closed-loop feedback system for maintaining accuracy.
3Measurement precision
If calibration operations are performed frequently to reduce drift, then heading accuracy is improved, but navigation time is increased due to calibration stops
Solution Approach 1:
Calibration locations are pre-identified and stored in a calibration map during system setup or initial operation. This preliminary action allows the system to plan calibration stops in advance along the navigation route, selecting locations that minimize disruption to the overall navigation timeline while ensuring adequate calibration opportunities.
Solution Approach 2:
The system performs calibration operations only at specific calibration map locations rather than continuously or at every position. This partial action approach calibrates sensors at strategically selected points along the route, providing sufficient drift correction without requiring calibration stops at every possible location, thereby balancing accuracy with navigation efficiency.
Data Source
AI summary
Aspects of the present invention relate to systems and methods for calibrating an autonomous navigation system. According to a first aspect of the present invention, calibration of the autonomous navigation system may be controlled by a calibration map.