IMU Azimuth Estimation Using Non-Holonomic Motion Constraints
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Solution Overview
Problem
Existing azimuth estimation methods using inertial measurement units (IMU) suffer from accuracy limitations and require external sensors like GPS or speed sensors, limiting their form factor and increasing costs.
Innovation Solution
An information processing apparatus and method that calculates accelerations and velocities in a reference coordinate system, utilizing non-holonomic constraints to specify a rotation component and absolute azimuth, enabling high-accuracy azimuth estimation without external sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS or external attitude sensors are used for azimuth estimation during movement, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The invention extracts and eliminates the dependency on external sensors (GPS, attitude sensors) by deriving all necessary information from the IMU's acceleration and angular velocity data through inertial navigation calculations and non-holonomic constraint optimization
Solution Approach 2:
The system serves itself by using only the IMU sensor to estimate azimuth during movement, without requiring external assistance from GPS or other sensors. The optimization unit self-corrects errors by applying non-holonomic constraints to the inertial navigation data
2Device complexity
If IMU alone is used for azimuth estimation without external sensors, then device complexity is reduced, but measurement precision deteriorates due to error diffusion
Solution Approach 1:
The invention introduces a feedback mechanism where the optimization unit continuously monitors the inertial navigation calculation results and applies corrections based on non-holonomic constraints. The system feeds back error correction information to improve subsequent azimuth estimates, preventing error diffusion accumulation
Solution Approach 2:
The invention changes the processing parameters of the IMU data by applying optimization calculations that incorporate non-holonomic constraints. This transforms the raw inertial navigation data into corrected acceleration and angular velocity values that maintain accuracy over time
3Device complexity
If probability theory-based estimation is used with IMU alone, then device complexity is reduced, but measurement precision is limited
Solution Approach 1:
The invention replaces probability theory-based statistical estimation with a deterministic mechanical/mathematical system based on inertial navigation calculations and non-holonomic constraints. This substitution provides more accurate and reliable azimuth estimation while maintaining simplicity
Data Source
AI summary
There is provided an information processing apparatus, an information processing method, and a program capable of estimating an azimuth of a mobile object that is moving by an inertial measurement unit (IMU) alone with high accuracy. At least one of an acceleration and a velocity of a mobile object in a reference coordinate system is calculated on the basis of inertial navigation calculation, at least one of an acceleration and a velocity of the mobile object coordinate system that is a coordinate system of the mobile object is calculated from at least one of the acceleration and the velocity of the reference coordinate system, and a rotation component or an absolute azimuth is specified on the basis of at least one of the acceleration and the velocity of the mobile object coordinate system and reference information of at least one of an acceleration and a velocity serving as a non-holonomic constraint condition that constrains a degree of freedom of at least one of six axes related to an attitude and a velocity of the mobile object. The present disclosure can be applied to an inertial navigation system.