Inspection UAV Flight Control Using Depth Sensing for Collision Avoidance
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Solution Overview
Problem
Current methods for controlling unmanned aerial vehicles (UAVs) during inspection flights require manual determination of object positions, limiting automation and increasing the risk of collisions.
Innovation Solution
The method involves recording image and depth data using a camera and depth sensor on the UAV, processing them with artificial intelligence to recognize objects, determine position coordinates, and generate collision-avoiding flight trajectories, enabling fully automated inspection flights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual determination of object positions is used, then the system is simpler to implement, but the extent of automation is reduced and collision risk increases
Solution Approach 1:
The UAV system performs self-localization by autonomously determining its own position and the object's position using onboard sensors (camera, depth sensor, inertial measurement unit) and processing units. The system automatically executes image analysis, sensor data fusion, and flight trajectory determination without external manual intervention, enabling fully automated inspection flights while reducing collision risk through real-time autonomous navigation.
2Reliability
If manual determination of object positions is used, then the device complexity is lower, but the safety and collision avoidance capability deteriorates
Solution Approach 1:
The system continuously captures real-time sensor data from the camera, depth sensor, and inertial measurement unit during flight, processes this data to determine current position and object location, and automatically adjusts the flight trajectory based on this feedback. This closed-loop control enables dynamic collision avoidance by constantly monitoring the environment and adapting the flight path to maintain safe distances from the inspection object.
Solution Approach 2:
The patent replaces manual mechanical navigation with automated sensor-based positioning and control. Instead of manual visual observation and manual control input, the system uses electronic sensors (camera, depth sensor, GPS, inertial measurement unit) and automated processing to determine position, calculate flight trajectories, and control the UAV, thereby improving safety and collision avoidance capability.
3Productivity
If fully automated inspection flight is implemented, then productivity and efficiency are improved, but the device complexity and processing requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-processing sensor data during the approach phase and before the actual inspection flight. Image analysis and object recognition are executed in advance to identify the inspection target and determine its position coordinates. Flight trajectories are pre-calculated based on preliminary sensor data fusion, allowing the UAV to execute automated inspection flights more efficiently without real-time processing delays.
Data Source
AI summary
The invention relates to a method for controlling an inspection flight of an unmanned aerial vehicle for purposes of inspecting an object, and to an inspection unmanned aerial vehicle. The method comprises the following: recording of image data for an object by means of a camera device on an unmanned aerial vehicle during a first flight path in a flight coordinates system in the vicinity of the object; and recording of depth data by means of a depth sensor device on the unmanned aerial vehicle, wherein the depth data indicate distances between the unmanned aerial vehicle and the object during the first flight path. Flight trajectory coordinates for the unmanned aerial vehicle are determined for purposes of inspecting the object, which avoids collision with the object.