Visual Waypoint Positioning for Precise UAV Navigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Precise navigation of unmanned aerial vehicles (UAVs) and other movable objects is challenging due to the inaccuracy of global navigation satellite systems, especially in environments with poor contrast or featureless surfaces, leading to inaccurate waypoint determination and navigation.
Innovation Solution
A method and system that enables movable objects to navigate by observing their surroundings, identifying points of interest, and calculating relative positions using image coordinates and vectors, allowing them to avoid virtual walls or fences and accurately reach selected waypoints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If global navigation satellite systems are used for positioning, then the movable object can navigate autonomously, but the positioning accuracy is insufficient due to inherent inaccuracy
Solution Approach 1:
The patent combines multiple positioning methods: GNSS for coarse positioning, visual odometry for relative position calculation, and map matching for waypoint determination. This integration compensates for the limitations of each individual method, achieving both high accuracy and reliability in navigation.
Solution Approach 2:
The system introduces an intermediary calculation layer that processes GNSS coordinates through visual odometry and map matching algorithms. This intermediary processing transforms inaccurate raw GNSS data into precise relative positions and accurate waypoints, resolving the contradiction between autonomy and accuracy.
2Measurement precision
If image recognition is used to guide the movable object through terrain, then navigation can be improved, but it becomes difficult in environments with poor contrast or featureless surfaces
Solution Approach 1:
The system performs preliminary actions by pre-processing images to enhance features, using preliminary map data to predict terrain characteristics, and preparing multiple navigation strategies in advance. This allows the system to adapt to poor contrast environments by switching to alternative methods like terrain contour analysis or elevation-based navigation.
Solution Approach 2:
The patent changes parameters such as image processing thresholds, feature detection sensitivity, and navigation algorithm selection based on environmental conditions. When contrast is poor, the system adjusts parameters to rely more on structural features or alternative sensing methods, maintaining adaptability across diverse terrains.
3Ease of operation
If publicly available maps are used to determine waypoints, then navigation can be established, but the low resolution leads to inaccurate guidance and location determination
Solution Approach 1:
The system transitions from two-dimensional map coordinates to three-dimensional spatial positioning by incorporating elevation data and relative position calculations. This dimensional enhancement allows accurate waypoint determination even when map resolution is low, as the system uses vertical dimension information and real-time relative positioning to compensate for horizontal precision limitations.
Data Source
AI summary
A system for navigation includes a movable object. The movable object is configured to navigate to a first position and, while at the first position, determine a second position based on a selected point on an image.