Visual Target Navigation for GNSS-Denied Mobile Platforms
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Solution Overview
Problem
Existing navigation systems for unmanned vehicles (UVs) rely heavily on Global Navigation Satellite Systems (GNSS), which may not be available or desirable in certain scenarios, leading to navigational control loss and potential damage to the UV and jeopardizing missions.
Innovation Solution
A GNSS-free navigation system that uses image data and distance sensing to determine direction and displacement vectors, allowing UVs to navigate autonomously to a target without GNSS, using image analysis and distance sensing to refine position estimates through a model displacement vector.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GNSS-based navigation is used, then navigation accuracy is improved, but the system becomes unreliable in areas without GNSS coverage
Solution Approach 1:
The system changes the navigation parameters from satellite-based coordinates to visual feature-based positioning. By detecting visual features in the environment and calculating position based on feature matching and displacement vectors, the system achieves reliable navigation in GNSS-denied environments while maintaining acceptable accuracy
Solution Approach 2:
Visual features serve as an intermediary between the UV and the target location. Instead of directly using GNSS signals, the system detects environmental features, tracks their displacement, and uses this information to infer position and navigate to the target, creating a reliable alternative navigation path
2Reliability
If GNSS-free navigation is implemented, then system reliability in denied areas is improved, but navigation precision deteriorates
Solution Approach 1:
The system continuously detects visual features, calculates displacement vectors from detected feature positions, and uses this feedback to update position estimates and adjust navigation. This closed-loop feedback mechanism improves navigation precision by constantly refining the position calculation based on actual observed feature displacement
Solution Approach 2:
The system transitions from two-dimensional GNSS coordinate navigation to three-dimensional visual feature space navigation. By utilizing depth information from distance sensing devices and spatial relationships among multiple visual features, the system compensates for precision limitations and achieves accurate positioning in GNSS-denied environments
3Adaptability or versatility
If visual feature detection and distance sensing are used, then navigation capability without GNSS is improved, but device complexity increases
Solution Approach 1:
The UV's existing sensors (cameras and distance sensors) are made multi-functional by using them for both environmental perception and navigation positioning. Instead of adding dedicated navigation hardware, the system repurposes existing sensors to detect visual features and calculate position, reducing overall system complexity while improving adaptability
Solution Approach 2:
The UV performs self-positioning by autonomously detecting visual features in its environment and calculating its own displacement and location. The system uses its own sensors to gather data and its own processor to compute position, eliminating the need for external infrastructure or additional specialized navigation equipment
Data Source
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AI summary
Aspects of embodiments to systems and methods for navigating a mobile platform using an imaging device on the platform, from a point of origin towards a target located in a scene, and without requiring a Global Navigation Satellite system (GNSS), by employing the following steps: acquiring, by the imaging device, an image of the scene comprising the target; determining, based on analysis of the image, a direction vector pointing from the mobile platform to the target; advancing the mobile platform in accordance with the direction vector to a new position; and generating, by a distance sensing device, an output as a result of attempting to determine, with the distance sensing device, a distance between the mobile platform and the target. The mobile platform advanced towards the target until the output produced by the distance sensing device is descriptive of a distance which meets a low-distance criterion.