Mobile Platform Navigation Using Vision and Distance Sensing
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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 accurate in certain situations, leading to potential collisions and mission failures due to lack of satellite line of sight, signal discontinuation, or intentional avoidance.
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 by acquiring images, analyzing them to determine direction vectors, and employing distance sensing to adjust and refine the navigation path, ultimately calculating a model displacement vector for accurate positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GNSS is used for navigation, then navigation accuracy is improved, but reliability deteriorates due to signal availability issues
Solution Approach 1:
The patent introduces visual landmarks and distance sensing devices as intermediary elements between the UV and its destination. Instead of directly relying on GNSS signals, the system uses detectable features in the environment (landmarks) and active sensing (distance sensors) to mediate the navigation process, providing a reliable alternative when satellite signals are unavailable.
Solution Approach 2:
The patent replaces the passive mechanical system of GNSS reception with an active visual-mechanical system. The UV actively captures images, processes visual information to identify landmarks, and uses distance sensing devices to measure distances, substituting the satellite-based mechanical system with a self-contained visual-mechanical navigation approach.
2Reliability
If GNSS-free navigation is implemented, then reliability is improved, but measurement precision deteriorates
Solution Approach 1:
The patent merges multiple navigation techniques into a unified system: visual landmark recognition, distance sensing device measurements, and vector calculations are combined to determine the UV's position and orientation. This integration of multiple independent methods achieves high positional accuracy while maintaining navigation independence from GNSS.
Solution Approach 2:
The system continuously captures images, identifies landmarks, measures distances, and recalculates position and orientation vectors in real-time. This closed-loop feedback mechanism allows the UV to maintain accurate positioning by constantly updating its navigation data based on current environmental observations and sensor readings.
3Adaptability or versatility
If image analysis is used to determine direction vectors, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent segments the navigation task into distinct processing stages: image capture, landmark identification, direction vector calculation, and navigation command generation. By dividing the complex image analysis process into manageable segments, the system achieves high environmental adaptability while keeping processing complexity organized and manageable through modular architecture.
Data Source
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.