Passive UAV Docking Nest for GPS-Free Visual Landing
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Solution Overview
Problem
Existing unmanned aerial vehicle (UAV) base stations are large, mechanically complex, and expensive, requiring accurate GPS positioning and complex mechanical methods for docking, which limits their functionality in GPS-denied environments and necessitates frequent human intervention for battery swapping.
Innovation Solution
A small, passive funnel-shaped nest with spring contacts and visual tags, supplemented by larger fiducials, enables precise UAV landings and automated battery charging, using visual tracking and control software to maintain accurate positioning and communication in various conditions, with a retractable arm to minimize turbulence and a secure enclosure for protection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If large base station enclosures are used with complex mechanical methods for docking, then UAV landing and battery swapping can be achieved, but system size, complexity, and cost increase significantly
Solution Approach 1:
The patent extracts and removes complex mechanical docking mechanisms from the base station system. Instead of using large enclosures with articulated robotic arms and complex alignment mechanisms, the invention uses a simple landing pad with visual fiducials that guide the UAV to dock automatically, eliminating the need for complex mechanical intervention while maintaining reliable docking functionality
Solution Approach 2:
The patent replaces complex mechanical docking methods with a vision-based guidance system. Visual fiducials on the landing pad are detected by the UAV's camera system, and computer vision algorithms calculate the precise docking position and orientation, substituting mechanical alignment mechanisms with optical and computational methods that reduce system complexity
2Measurement precision
If accurate GPS positioning is required for UAV landing, then precise positioning can be achieved, but functionality in GPS-denied environments is lost
Solution Approach 1:
The patent introduces visual fiducials as an intermediary reference system between the UAV and the landing pad. These fiducials serve as local positioning markers that the UAV's vision system can detect and use to calculate precise relative position and orientation, providing a GPS-independent reference frame that enables accurate docking in GPS-denied environments
Solution Approach 2:
The patent transitions from relying solely on global GPS positioning to using local visual fiducial detection in the image space. By detecting fiducial markers in the UAV's camera field of view and calculating their position in the image plane, the system creates a new dimensional reference system that provides precise localization independent of GPS availability
3Extent of automation
If automated docking systems are implemented, then human intervention is reduced, but system complexity and cost increase
Solution Approach 1:
The patent implements a self-service docking system where the UAV autonomously navigates to the landing pad using visual fiducial guidance and automatically aligns itself for docking. The system requires no external mechanical assistance, robotic arms, or complex automated handling mechanisms - the UAV performs the docking maneuver independently by following visual cues and executing autonomous flight control, achieving high automation with minimal added complexity
Data Source
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AI summary
Described herein are systems for automated docking of an unmanned aerial vehicle. For example, some systems include an unmanned aerial vehicle including a propulsion mechanism, an image sensor, and processing apparatus; and a dock including a landing surface configured to hold the unmanned aerial vehicle and a fiducial on the landing surface, wherein the processing apparatus is configured to: control the propulsion mechanism to cause the unmanned aerial vehicle to fly to a first location in a vicinity of the dock; access one or more images captured using the image sensor; detect the fiducial in at least one of the one or more images; determine a pose of the fiducial based on the one or more images; and control, based on the pose of the fiducial, the propulsion mechanism to cause the unmanned aerial vehicle to land on the landing surface.