Pose Graph Optimization for Position Measurement Timing Mismatch
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Solution Overview
Problem
Existing position measurement apparatuses face challenges in achieving accurate position measurement due to timing mismatches between inertial measurement unit data and satellite navigation signals, leading to potential deviations in correspondence between inertial and satellite navigation positions.
Innovation Solution
A position measurement apparatus that includes an inertia detection portion, an inertial navigation process portion, a position measurement process portion, and an integration process portion. The integration process forms a pose graph using state information from both inertial and position measurements, optimizing loop confinement to systematically correct errors and improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If position measurement is performed using inertial navigation and satellite navigation separately, then position information can be obtained from each system, but timing mismatches between the two systems cause deviations in correspondence relationship
Solution Approach 1:
The patent combines inertial navigation and satellite navigation into a unified pose graph optimization framework. Both navigation systems are integrated by forming a pose graph that includes nodes from both systems and optimizing loop constraints that relate them, thereby achieving synchronized and consistent position measurement without timing mismatch deviations.
Solution Approach 2:
The patent implements feedback by using loop confinement optimization to correct systematic errors. The optimization process computes corrections based on loop constraints and applies them back to the pose estimates from both inertial and satellite navigation systems, continuously improving accuracy by feeding back error corrections.
2Measurement precision
If high-performance inertia detection systems are used to improve measurement accuracy, then position measurement precision improves, but system cost increases
Solution Approach 1:
The patent introduces pose graph optimization as an intermediary computational framework that mediates between inertial and satellite navigation data. This intermediary process corrects systematic errors through loop constraints, allowing the use of lower-performance (and lower-cost) inertia detection systems while maintaining high position measurement accuracy through mathematical optimization rather than hardware performance.
Data Source
AI summary
A position measurement apparatus includes a position measurement signal reception portion, an object detection portion, an inertia detection portion, a first position estimation portion, a second position estimation portion, an inertial navigation process portion, and an information integration portion. The inertial navigation process portion outputs third information of a time series of a movable body by inertial navigation based on inertia information that is output from the inertia detection portion. The first position estimation portion and the second position estimation portion output first information and second information by a position measurement based on information output from the position measurement signal reception portion and the object detection portion. The information integration portion forms a pose graph using the first information and the second information that relatively constrain a predetermined zone of a plurality of third information of the time series and outputs a systematic error of the third information by optimization of a loop confinement in the predetermined zone.