UAV Navigation Assistance Data for Dynamic Route Planning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The integration of drones into airspace poses challenges, including collisions with obstacles or other aircraft, and unauthorized flights over restricted areas due to lack of knowledge about airspace regulations and restrictions.
Innovation Solution
A method for determining a flight route for unmanned aerial vehicles (UAVs) using navigation assistance data that includes flight-specific information such as UAV characteristics, obstacles, permitted zones, hazards, and regulations, allowing for dynamic route adjustment during flight.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If drones are introduced into airspace for various missions, then operational flexibility and cost effectiveness are improved, but safety risks increase due to potential collisions with obstacles, airplanes, helicopters, or other drones
Solution Approach 1:
The system performs preliminary actions by obtaining airspace information and generating flight routes before the drone begins its mission. The server receives the mission request, retrieves relevant airspace data, evaluates flight risks, and determines a safe flight route in advance, ensuring safety considerations are integrated into the mission planning phase rather than reacting to hazards during flight
Solution Approach 2:
A server acts as an intermediary between the drone and the complex airspace environment. The server receives mission requests from drones, processes airspace information from multiple sources, evaluates flight risks, and returns recommended flight routes. This intermediary consolidates disparate data sources and provides a unified safety assessment, reducing the burden on individual drones while improving overall system safety
2Ease of operation
If drones operate without knowledge of airspace restrictions and regulations, then ease of operation is improved, but compliance issues arise from unauthorized flights over restricted areas
Solution Approach 1:
The system enables drones to self-serve by automatically obtaining and processing airspace information without requiring manual input from operators. The drone submits its mission request with basic parameters, and the server autonomously retrieves airspace restrictions, evaluates compliance, and generates a compliant flight route, maintaining ease of operation while ensuring regulatory compliance
Solution Approach 2:
The system performs preliminary compliance checks by obtaining airspace information and evaluating flight routes before the drone begins its mission. The server retrieves restricted area data, evaluates the proposed route against regulations, and modifies the route if necessary to ensure compliance with airspace restrictions before the drone deploys
3Device complexity
If flight routes are determined without considering flight-specific information such as UAV characteristics, then device complexity is reduced, but navigation accuracy and safety are compromised
Solution Approach 1:
The system applies local quality by customizing flight routes according to the specific characteristics of each drone and mission. Instead of using a generic routing algorithm, the server retrieves drone-specific parameters such as flight altitude, speed, and payload information, and uses these to evaluate flight risks and determine an optimized route tailored to that particular drone's capabilities and mission requirements
Solution Approach 2:
The system utilizes parameter changes by incorporating flight-specific parameters into the route determination process. The server retrieves parameters such as drone type, flight altitude, speed, and payload information, and uses these varying parameters to evaluate different route options and select the most appropriate flight path that optimizes both safety and mission effectiveness for each specific scenario
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Methods, systems, computer-readable media, and apparatuses for determining a flight route for a flight of an unmanned aerial vehicle (UAV) are presented. The flight-specific route for the UAV is determined dynamically during the flight or in advance before the flight, using navigation assistance data that includes flight-specific navigation assistance data for a plurality of geographic zones determined based on flight-specific information. The flight-specific navigation assistance data includes flight-specific ranking data for the plurality of geographic zones that can be used by the UAV or a server to determine the flight route.