eVTOL Flight Path Planning Using Segmented Deterministic Logic
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Solution Overview
Problem
Existing path planning methods for aerial vehicles, particularly eVTOLs, lack flexibility and determinism, making them unsuitable for highly regulated areas with high safety requirements or environments with high operational risk.
Innovation Solution
An all-inclusive method for safe and efficient operation of eVTOLs, involving pre-processing data on the ground, transferring pre-planned results on board, combining them with real-time sensor data using deterministic decision logic, and controlling the vehicle along a generated flight path.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If optimization or machine learning based approaches are used for path planning, then flexibility is improved, but determinism and inspectability deteriorate
Solution Approach 1:
The path planning system is segmented into multiple independent planning methods, each responsible for specific operational areas or flight phases. This allows deterministic validation of individual segments while maintaining overall system flexibility through selective combination of different planning approaches.
Solution Approach 2:
The system dynamically selects and switches between different planning methods based on the current operational area and flight phase. This dynamic adaptation enables the system to maintain determinism when using pre-validatable methods while gaining flexibility when switching to optimization-based approaches, resolving the contradiction between these two requirements.
2Reliability
If dedicated planning approaches are used for specific applications, then reliability is improved, but adaptability to new circumstances deteriorates
Solution Approach 1:
The system implements a universal framework that can accommodate multiple dedicated planning approaches for different applications. Each planning method can be validated for its specific purpose while the overall system maintains adaptability through the ability to select and combine different methods based on operational requirements.
3Power
If extensive data pre-processing is performed on the ground, then real-time computing demands are reduced, but loss of time before flight increases
Solution Approach 1:
Extensive data pre-processing and planning are performed in advance on the ground before flight. This preliminary action transfers significant computational workload to the pre-flight phase, reducing real-time computing demands during flight operations while accepting the trade-off of increased pre-flight preparation time.
Data Source
AI summary
An all-inclusive method for planning the operation of an aerial vehicle, in particular an eVTOL, which operation is divided into different operational areas each with its own individually validatable and inspectable planning methodology, including (i) pre-processing data on a computer basis on the ground before takeoff of the aerial vehicle; (ii) taking along pre-planned results of the data pre-processing in the form of a database (33, 44) on board the aerial vehicle, preferably after transferring the pre-planned results into the database (33, 44) on board the aerial vehicle; (iii) combining the pre-planned results by means of a computer-based decision logic (28) with planning steps at the flying time in accordance with a state of the aerial vehicle recorded by sensors for generating a current flight path; and (iv) controlling the aerial vehicle along the current flight path.