Collaborative Visual-Inertial Mapping for GPS-Denied Localization
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Solution Overview
Problem
Existing navigation systems lack the capability to accurately localize platforms in GPS-denied environments, leading to increased localization errors that hinder situation awareness and collaborative tasks requiring precise location information.
Innovation Solution
A collaborative navigation and mapping subsystem that uses a combination of camera images, IMU tracking data, and shared information among multiple platforms to construct and match geo-referenced visual features, determining platform pose through IMU measurements and relative motion information, even in GPS-denied conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GPS-based navigation is used, then navigation accuracy is maintained, but navigation fails in GPS-denied environments
Solution Approach 1:
The patent combines multiple navigation approaches (visual odometry, IMU tracking, and map matching) into a unified navigation system. This integration allows the system to maintain reliable navigation in GPS-denied environments by merging the strengths of different methods while compensating for their individual weaknesses through sensor fusion and collaborative processing
Solution Approach 2:
The patent introduces pre-built maps of geo-referenced visual features as an intermediary between the camera system and the navigation solution. These maps serve as a reference framework that enables accurate localization without direct GPS signals, acting as a mediator that translates visual observations into precise position and orientation estimates
2Measurement precision
If visual feature matching is used for localization, then accuracy is maintained in GPS-denied environments, but system complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-building maps of geo-referenced visual features before navigation operations. This preprocessing step creates a ready-to-use reference framework that simplifies real-time localization, as the system only needs to match observed features against the pre-established map rather than building and processing complex data structures on-the-fly
Solution Approach 2:
The patent segments the navigation system into distinct functional modules: visual feature extraction, feature matching, IMU data processing, and pose estimation. This modular segmentation allows each component to be optimized independently and facilitates collaborative processing across multiple platforms, reducing overall system complexity through division of labor
3Reliability
If multiple platforms share information collaboratively, then navigation robustness improves, but communication requirements and system complexity increase
Solution Approach 1:
The patent implements a universal communication framework where platforms exchange standardized visual feature and pose information that can be used by any participating platform. This multi-functional data exchange protocol enables robust collaborative navigation without requiring platform-specific communication infrastructure, as the same data format serves multiple purposes across different devices
Data Source
AI summary
During GPS-denied/restricted navigation, images proximate a platform device are captured using a camera, and corresponding motion measurements of the platform device are captured using an IMU device. Features of a current frame of the images captured are extracted. Extracted features are matched and feature information between consecutive frames is tracked. The extracted features are compared to previously stored, geo-referenced visual features from a plurality of platform devices. If one of the extracted features does not match a geo-referenced visual feature, a pose is determined for the platform device using IMU measurements propagated from a previous pose and relative motion information between consecutive frames, which is determined using the tracked feature information. If at least one of the extracted features matches a geo-referenced visual feature, a pose is determined for the platform device using location information associated with the matched, geo-referenced visual feature and relative motion information between consecutive frames.