Drone Landing Zone Localization for Remote Site Pre-Assessment
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Solution Overview
Problem
Existing methods for determining drone landing locations in emergency situations are often inefficient, especially in remote areas, leading to cost and time delays when the initial landing site proves unsuitable, as they require on-site drone presence and may not account for real-time obstructions or safety hazards.
Innovation Solution
A system and method utilizing a mobile device and vehicle sensors, including cameras and GPS, to pre-assess and provide location-specific information for drone landing, using augmented reality and image recognition to determine feasible landing areas, and enabling communication between the drone, service provider, and user to calculate landing space and clearance, and guide the drone to a safe landing site.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the drone is dispatched to a remote location without pre-assessment, then the response time is reduced, but the landing feasibility is compromised leading to delays and cost increases
Solution Approach 1:
The system performs preliminary assessment of the landing area using images and sensor data from the vehicle and mobile device before the drone is dispatched. This pre-assessment identifies suitable landing zones and potential obstacles, ensuring that the drone can successfully land when it arrives, thus resolving the contradiction between fast response and reliable landing.
2Measurement precision
If the drone performs on-site landing assessment, then the landing accuracy is improved, but the time and cost are increased due to the need for on-site presence
Solution Approach 1:
The system creates a digital copy of the landing area using images captured by cameras on the vehicle and mobile device. This digital representation allows the drone controller to perform detailed landing assessments remotely without requiring the drone to be physically present at the site, thereby maintaining high landing accuracy while eliminating the time loss associated with on-site assessment.
3Device complexity
If pre-defined static landing locations are used, then the system complexity is reduced, but the adaptability to real-time conditions is worsened
Solution Approach 1:
The system transitions from static pre-defined landing locations to dynamic landing zone identification. The drone controller receives real-time image and sensor data from the vehicle and mobile device, allowing it to identify and adapt to actual landing conditions at the scene. This dynamic approach maintains reasonable system complexity while significantly improving adaptability to real-time conditions.
Data Source
AI summary
Systems and methods for service drone landing zone operations are disclosed herein. An example method includes determining location-specific information for a location, the location-specific information including at least images of the location from at least one of a vehicle or a mobile device at the location, determining a landing area for a drone at the location using the location-specific information, receiving localizing signals from at least one of the vehicle or the mobile device as the drone approaches the location, and causing the drone to land in the landing area using the localizing signals.