Visual Navigation Performance Estimation for Obstructed Drone Paths
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Solution Overview
Problem
Existing navigation systems for vehicles, particularly drones, face challenges in accurately estimating navigation performance due to factors like obstructions, light, and variations in color, which can lead to inaccurate decision-making and potential accidents.
Innovation Solution
A method for path navigation accuracy estimation that determines the degree of obstruction for objects in visual content, calculates co-visibility based on the vehicle's pose and obstructions, and estimates visual navigation performance at operational points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If navigation decisions are made based on images captured by cameras, then navigation automation is achieved, but navigation accuracy deteriorates due to obstructions, light variations, and color variations affecting image representativeness
Solution Approach 1:
The system performs preliminary estimation of visual navigation performance at different operational points before executing navigation decisions. By evaluating factors such as obstruction degrees, co-visibility, and image representativeness in advance, the system can identify optimal navigation paths that maintain high accuracy while fully automated
Solution Approach 2:
The system establishes a feedback loop where navigation performance is continuously estimated based on captured images and environmental factors. This feedback mechanism allows the system to adjust navigation decisions in real-time, compensating for image quality issues caused by obstructions, light variations, and color variations
2Measurement precision
If navigation paths are planned to avoid low-performance areas, then navigation accuracy is improved, but navigation time increases due to additional planning and evaluation
Solution Approach 1:
The system pre-calculates visual navigation performance metrics for multiple potential operational points and paths before navigation begins. This preliminary evaluation creates a performance map that guides real-time decisions, avoiding the need for time-consuming calculations during actual navigation while ensuring high accuracy
Solution Approach 2:
The system dynamically adjusts navigation paths based on real-time performance estimation. By continuously evaluating visual conditions and comparing against pre-calculated performance data, the system can quickly adapt to changing environments without exhaustive replanning, balancing accuracy with time efficiency
Data Source
AI summary
A system and method for path navigation accuracy estimation. A method includes determining a degree of obstruction for each of a plurality of objects shown in visual content, wherein the degree of obstruction for each object represents a degree to which the object will obstruct visibility by a vehicle capturing visual content in an environment where the vehicle is navigating and the plurality of objects are disposed; determining, for each of a plurality of operational points, a co-visibility of the vehicle at the operational point based on a pose of the vehicle at the operational point and the degree of obstruction for each of the objects which is within view of the vehicle at the operational point; and estimating a visual navigation performance at each of the operational points based on the co-visibility determined for the operational point.