Pose Estimation Using Sensor Fusion and Terrain Data
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Solution Overview
Problem
Current GPS/INS solutions for pose estimation in outdoor environments lack customization and accuracy, particularly in arbitrary outdoor settings, and fail to provide stable altitude measurements, leading to performance limitations.
Innovation Solution
The system employs a combination of sensors such as cameras, accelerometers, gyroscopes, magnetometers, barometric pressure sensors, and GPS receivers, along with digital terrain and elevation data, using an Extended Kalman Filter (EKF) to calculate precise pose estimation, and incorporates a database for geodetic coordinates, allowing for enhanced accuracy and rejection of magnetic disturbances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional GPS/INS solutions are used for pose estimation, then the system is simple to implement, but the measurement precision and reliability are insufficient for arbitrary outdoor environments
Solution Approach 1:
The patent combines GPS/INS system with additional sensors (accelerometers, gyroscopes, magnetometers, barometric pressure sensors) and digital terrain data to create a hybrid pose estimation system. This merging of multiple measurement systems and data sources resolves the contradiction by achieving higher measurement precision through sensor fusion while managing complexity through integrated processing.
Solution Approach 2:
The patent introduces an Extended Kalman Filter (EKF) as an intermediary processing layer that fuses data from multiple sensors and digital terrain data. The EKF acts as a mediator that combines measurements from GPS, inertial sensors, and terrain data to produce accurate pose estimates, resolving the precision-complexity contradiction through sophisticated data integration.
2Adaptability or versatility
If GPS/INS systems operate in arbitrary outdoor environments, then the adaptability is improved, but the reliability and stability of altitude measurements deteriorate
Solution Approach 1:
The patent uses digital terrain and elevation data as an intermediary reference to improve altitude measurement reliability. By comparing barometric pressure sensor readings with terrain data from external sources, the system resolves contradictions between environmental adaptability and measurement reliability, providing stable altitude estimates even in challenging outdoor conditions.
Solution Approach 2:
The system implements feedback mechanisms where pose estimation results are continuously refined using digital terrain data and sensor measurements. The EKF processes feedback from multiple sources including barometric pressure changes and terrain elevation data to maintain reliable altitude measurements across diverse environments, resolving the adaptability-reliability contradiction.
3Measurement precision
If magnetometer measurements are used for pose estimation, then the orientation accuracy is improved, but magnetic disturbances cause harmful effects that worsen measurement reliability
Solution Approach 1:
The patent converts the harmful effect of magnetic disturbances into a beneficial detection mechanism. By monitoring magnetometer readings and identifying patterns consistent with magnetic disturbances, the system can detect when measurements are corrupted and take corrective action, such as rejecting affected measurements or switching to alternative orientation sources, thus resolving the precision-harmful factors contradiction.
Solution Approach 2:
The system uses other sensors (accelerometers, gyroscopes) and digital terrain data as intermediary references to compensate for magnetometer measurements affected by magnetic disturbances. When magnetic interference is detected, the EKF relies more heavily on inertial measurements and terrain data to maintain orientation accuracy, resolving the contradiction between utilizing magnetometer precision and avoiding magnetic harmful effects.
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 approach enables accurate and customizable pose estimation, providing stable altitude measurements and improved performance by integrating kinematic constraints and digital terrain data, surpassing the limitations of traditional GPS/INS systems.
Implementation Method 1
a barometric pressure sensor
Implementation Method 2
a 3-axis magnetometer... the processing module detects the presence of magnetic disturbances and, if detected, rejects magnetometer measurements corresponding to magnetic disturbances
Implementation Method 3
an Extended Kalman Filter (EKF) to calculate precise pose estimation
Data Source
AI summary
The described technology regards an augmented reality system and method for estimating a position of a location of interest relative to the position and orientation of a display, including receiving and selectively filtering a plurality of measurement vectors from a rate-gyroscope. Systems of the described technology include including a plurality of sensors, a processing module or other computation means, and a database. Methods of the described technology use data from the sensor package useful to accurately render graphical user interface information on a display.