AI-Guided UAV Inspection Flight Path for Collision Avoidance
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Solution Overview
Problem
Current methods for controlling unmanned aircraft during inspection flights lack extensive automation, requiring manual initial overflights to determine object positions for subsequent trajectory determination, which limits the fully automatic execution of inspection tasks.
Innovation Solution
The method involves acquiring image and depth data using a camera and depth sensor, processing them with AI for object recognition, and fusing sensor data to determine object reference points and flight path coordinates, enabling collision-avoiding inspection flights without manual positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual initial overflights are performed to determine object positions, then object position accuracy is improved, but automation extent deteriorates
Solution Approach 1:
The system performs self-positioning by automatically determining its own location through image recognition of the object and sensor data fusion, eliminating the need for manual initial overflights. The evaluation unit processes image data and sensor signals to autonomously calculate the unmanned aerial vehicle's position relative to the object, achieving both high accuracy and full automation.
Solution Approach 2:
The patent replaces manual mechanical positioning operations with an automated optical and computational system. Image sensors capture visual information of the object, AI-based recognition identifies object features, and sensor data fusion algorithms compute precise position coordinates, substituting human-operated mechanical navigation with an automated sensing and computing system.
2Measurement precision
If sensor data fusion is performed for image data and depth data, then object recognition accuracy is improved, but device complexity deteriorates
Solution Approach 1:
The evaluation unit serves multiple functions: it processes image data for object recognition, fuses sensor data for depth estimation, determines object position coordinates, and calculates flight path coordinates. By consolidating these diverse functions into a single multi-functional evaluation unit, the system achieves high object recognition accuracy without proportionally increasing overall device complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for fully automated inspection flights by automatically determining object positions and trajectories, eliminating the need for manual initial overflights and enhancing collision avoidance and detailed area inspection capabilities.
Implementation Method 1
acquiring depth data by means of a depth sensor device arranged on the unmanned aerial vehicle, wherein the depth data indicate distances between the unmanned aerial vehicle and the object
Data Source
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AI summary
The invention relates to a method for controlling an inspection flight of an unmanned aerial vehicle for inspecting an object, and to an unmanned inspection aircraft. The method comprises: acquiring image data of an object by means of a camera device (1) on an unmanned aerial vehicle during a first flight movement in a flight coordinate system near the object; and acquiring depth data by means of a depth sensor device (2) on the unmanned aerial vehicle, wherein the depth data indicate distances between the unmanned aerial vehicle and the object during the first flight movement.When processing the image data and the depth data using an evaluation unit (8), the following is provided: performing an artificial intelligence-based image analysis for the image data, whereby the object is recognized from the image data using artificial intelligence-based image recognition, and pixel coordinates are determined in a camera coordinate system of the camera unit (1) for image pixels that are assigned to the recognized object; performing a sensor data fusion for the image data and the depth data, whereby depth data assignable to each image pixel of the object are determined, and at least one object reference point for the object is determined from the assigned depth data; and determining position coordinates for the at least one object reference point in the flight coordinate system, wherein the position coordinates indicate a position of the object in the flight coordinate system.Flight path coordinates are determined for the unmanned aircraft for a collision-avoiding inspection flight with respect to the object to inspect the object, taking into account the position coordinates for the at least one object reference point; and the unmanned aircraft is controlled during a second flight movement by means of a control device (9) such that the unmanned aircraft performs the collision-avoiding inspection flight in accordance with the flight path coordinates.