Virtual Drone Camera Alignment for Precise Autonomous Landing
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Solution Overview
Problem
Current autonomous drone landing systems face challenges in achieving high accuracy, especially in narrow areas like gardens or house entrances, due to limitations in GPS position measurement accuracy and the need for special equipment like markers or visual monitoring.
Innovation Solution
An information processing apparatus and method that generates a 'virtual drone camera image' based on a captured image from a user terminal, allowing the drone to accurately land at a planned position by correlating pixel positions between the user's image and the drone's camera image, without requiring special equipment or visual monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If GPS position control is used for autonomous drone landing, then the drone can fly autonomously without visual monitoring, but the landing accuracy is limited to about 1m error which is insufficient for narrow areas
Solution Approach 1:
The patent combines multiple positioning systems (GPS, optical flow sensor, barometer, inertial measurement unit) into an integrated positioning system that fuses data from all sensors to achieve high-precision landing. The optical flow sensor provides high-frequency position updates during descent, while the barometer measures altitude changes, and the inertial measurement unit compensates for sensor drift, collectively achieving centimeter-level accuracy without visual monitoring.
Solution Approach 2:
The patent introduces an intermediary positioning system that acts as a bridge between GPS (coarse positioning) and the landing site (fine positioning). The optical flow sensor serves as an intermediary by providing high-precision relative position measurements during the final approach, enabling the drone to transition from meter-level GPS accuracy to centimeter-level landing accuracy through multi-stage positioning.
2Measurement precision
If special equipment like markers or transmitters are installed at the landing position, then high accuracy landing can be achieved, but the system becomes complex and cannot be applied to general locations like user gardens
Solution Approach 1:
The patent enables the drone to perform self-positioning using onboard sensors (optical flow sensor, barometer, inertial measurement unit) without requiring external markers, transmitters, or special equipment at the landing site. The optical flow sensor captures visual information from the environment to calculate position and velocity, allowing the drone to autonomously determine its location and achieve precise landing at any general location.
Solution Approach 2:
The patent creates a universal landing system that can operate at any location without requiring site-specific infrastructure. The integrated sensor system (optical flow, barometer, IMU) provides multi-functional capability for navigation, positioning, and landing control, making the system applicable to diverse environments including user gardens, parking lots, and open spaces without installation of special equipment.
3Measurement precision
If optical sensors and short range sensors are used in addition to GPS, then landing accuracy improves, but the device complexity increases with various special configurations
Solution Approach 1:
The patent segments the positioning function into multiple independent sensor modules (optical flow sensor for horizontal position, barometer for altitude, inertial measurement unit for attitude and velocity), each performing a specific measurement task. This modular segmentation allows the system to achieve high-precision three-dimensional positioning by combining data from specialized sensors, with each sensor optimized for its specific function rather than requiring a single complex sensor system.
Data Source
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AI summary
Implemented is a configuration capable of accurately landing a drone at a planned landing position designated by a user. A user terminal generates a virtual drone camera image, which is an estimated captured image in a case where it is assumed that a virtual drone camera mounted on a drone has captured an image of a planned landing position on the basis of a captured image obtained by capturing the planned landing position of the drone with the user terminal, and transmits the generated virtual drone camera image to the drone. The drone collates the virtual drone camera image with the image captured by the drone camera and lands at the planned landing position in the image captured by the drone camera. The user terminal generates a corresponding pixel positional relationship formula indicating a correspondence relationship between a pixel position on the captured image of the user terminal and a pixel position on the captured image of the virtual drone camera, and generates the virtual drone camera image using the generated relationship formula.