Balcony Validation Using Visual Markers for Urban UAV Delivery
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Solution Overview
Problem
High-density urban spaces, particularly multi-level buildings, pose challenges for drone delivery due to the difficulty in identifying the correct delivery destination and navigating through obstructed areas, as traditional navigation methods like GPS are unreliable.
Innovation Solution
A system and method for validating and enrolling balconies into a parcel delivery service using unmanned aerial vehicles (UAVs), which involves identifying the correct balcony through aerial maps, user-provided images, and fiducial markers, and ensuring unobstructed paths for safe delivery, utilizing a combination of autonomous and semi-autonomous UAV operations with cloud-based servers and client-side applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional navigation methods (e.g., GPS) are used for drone delivery, then navigation simplicity is maintained, but navigation reliability deteriorates in urban canyon environments
Solution Approach 1:
The patent introduces visual markers (fiducial markers, QR codes, colored tapes) as intermediary objects placed on balconies and buildings to serve as navigation references for drones. These markers act as mediators between the drone's vision-based navigation system and the physical delivery locations, enabling reliable navigation in GPS-denied urban environments by providing detectable visual cues that the drone can track and use for precise positioning.
Solution Approach 2:
The patent replaces traditional GPS-based electronic navigation with a vision-based navigation system that uses optical markers and image recognition. This substitution allows the drone to navigate using visual information captured by onboard cameras and processed through computer vision algorithms, making the navigation system reliable in urban canyons where satellite signals are blocked.
2Adaptability or versatility
If drones deliver to multi-level buildings with many balconies, then delivery coverage is improved, but destination identification accuracy deteriorates due to low distinguishing features
Solution Approach 1:
The patent applies local quality by placing unique visual markers (fiducial markers, QR codes, colored tapes) on specific balconies and buildings. Each marker has distinct visual characteristics (patterns, colors, positions) that locally identify that particular delivery destination. This allows the drone to distinguish between multiple similar-looking balconies in multi-level buildings by detecting the unique visual signature at each location.
Solution Approach 2:
The patent utilizes color changes and visual pattern variations in the markers placed on different balconies. Different colored tapes, patterned fiducial markers, and QR codes provide visual differentiation that enables the drone's vision system to accurately identify and distinguish between multiple delivery destinations even when they appear similar from a distance or at different angles.
3Adaptability or versatility
If drones navigate through high-density urban spaces, then delivery accessibility is improved, but path obstruction increases
Solution Approach 1:
The patent employs preliminary action by using the mobile device application to capture reference images of the delivery location and generate a delivery route before the actual drone delivery. The system pre-identifies the balcony location, marks it with visual identifiers, and plans the navigation path in advance. This preliminary preparation enables the drone to efficiently navigate to the correct destination without needing to search or maneuver excessively during the actual delivery flight.
Data Source
AI summary
A technique for validating a balcony to receive delivery of a parcel via a UAV includes obtaining a first identification of a general location of the balcony; generating a first image representing a building including the balcony where the first image is selected based upon the location identified; obtaining a second identification or a confirmation of a precise location of the balcony in the building where the second identification or the confirmation are received in response to an end-user interaction with the first image; determining a deliverability score based at least in part on the precise location of the balcony; and indicating an enrollment status to the end-user where the enrollment status is generated based upon the deliverability score.