Multi-Coordinate Position Estimation Under LiDAR and GPS Reliability Loss
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Solution Overview
Problem
Existing localization technologies face challenges in achieving high accuracy when environmental conditions are unfavorable, such as high reflectance objects for LiDAR or shielding objects for GPS, leading to decreased reliability of position estimation results.
Innovation Solution
An information processing device that includes multiple estimators operating in different coordinate systems, an information acquisition part that selects the most reliable estimation results, and a coordinate transformer that adjusts positions to a common reference coordinate system, thereby improving position estimation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple localization methods (LiDAR, GPS) are used for position estimation, then localization accuracy is improved, but reliability decreases in environments with high reflectance objects or shielding objects
Solution Approach 1:
The system dynamically switches between different coordinate systems and estimation methods based on environmental conditions. When LiDAR reliability is low (high reflectance environment), the system transitions to using GPS-based estimation in a second coordinate system, and when GPS reliability is low (shielding environment), it uses LiDAR-based estimation. This dynamic adaptation resolves the contradiction by maintaining reliability while preserving accuracy through conditional selection of appropriate estimation methods.
Solution Approach 2:
The system changes the parameter of coordinate system reference based on environmental conditions. It transforms estimation results between a first coordinate system (map-centered) and a second coordinate system (vehicle-centered) depending on which localization method is more reliable in the current environment. This parameter change allows the system to maintain accurate position estimation by adapting to varying environmental conditions that affect different localization methods differently.
2Device complexity
If position estimation is performed using a single coordinate system, then system complexity is reduced, but adaptability to different environmental conditions deteriorates
Solution Approach 1:
The system implements multi-functionality by maintaining two coordinate systems with different reference points (map-centered first coordinate system and vehicle-centered second coordinate system). Each coordinate system is optimized for different localization methods and environmental conditions. The system can universally handle both LiDAR-based and GPS-based localization by transforming results between coordinate systems, thereby achieving environmental adaptability without excessive complexity.
Solution Approach 2:
The coordinate transformation function acts as an intermediary between the first and second coordinate systems. It enables seamless conversion of position estimation results between different reference frames, allowing the system to adapt to various environmental conditions while maintaining a unified position estimation interface. This intermediary mechanism provides adaptability without requiring complex reconfiguration of the entire system.
Data Source
AI summary
To improve accuracy of position estimation on the basis of a plurality of estimation results.An information processing device includes: a first estimator that estimates a self-position on the basis of a first coordinate system; a second estimator that estimates a self-position on the basis of a second coordinate system different from the first coordinate system; and an information acquisition part that, in a case where reliability of one of a first estimation result by the first estimator and a second estimation result by the second estimator in a coordinate system of the one estimation result is lower than a predetermined threshold, acquires self-position information on the basis of another estimation result.