UAV Guidance Modes for Independent IFR Flight Path Control
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Solution Overview
Problem
Existing autonomy systems for robots, particularly unmanned aerial vehicles (UAVs), are limited in extensibility as they are typically configured to address only one aspect of robot operation, such as automatic control, task allocation, or real-time data processing, which restricts their efficiency and operation flexibility.
Innovation Solution
The system provides guidance modes for UAVs that include lateral and vertical flight modes, along with air-ground transition modes, allowing for separate and independent operation under instrument flight rules (IFR), and enables transitions between these modes based on predefined conditions and additional input, enhancing the UAV's ability to follow cleared paths and execute missions autonomously.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing autonomy systems are configured to address only one aspect of robot operation, then the system design can focus on a narrow mission set, but the extensibility of the system is limited
Solution Approach 1:
The autonomy system is divided into separate functional modules including task allocation module, automatic control module, and real-time data processing module. Each module can be independently configured and activated based on specific mission requirements, allowing the system to address multiple aspects of robot operation simultaneously while maintaining manageable complexity through modular architecture
Solution Approach 2:
The system is designed with universal autonomy algorithms and software architecture that can handle multiple aspects of robot operation (task allocation, automatic control, data processing) within a single integrated platform. This multi-functional design allows the same system to be extended to various mission sets without requiring separate specialized systems for each function
2Productivity
If existing autonomy systems focus on a narrow mission set, then the system design can be optimized for specific tasks, but the efficiency and operation flexibility are restricted
Solution Approach 1:
The system employs dynamic task allocation and mission planning capabilities that allow real-time adjustment of operational parameters and task priorities based on changing mission requirements. This dynamic adaptability enables the system to maintain high efficiency across diverse operations by optimizing resource allocation and control strategies according to current operational context
Solution Approach 2:
The autonomy system incorporates real-time data processing and feedback mechanisms that continuously monitor operational performance and adjust control decisions accordingly. This feedback loop enables the system to maintain optimal efficiency across different mission types by learning from operational data and adapting control strategies to suit varying operational requirements
Data Source
AI summary
A method is provided for supporting operations of an unmanned air vehicle (UAV) on a flight in an airspace system. The method includes receiving instructions that describe a cleared path the UAV is authorized by an air navigation service provider (ANSP) to travel through the airspace system. The method includes determining guidance modes of the UAV based on the instructions, and engaging the guidance modes in which the UAV is caused to perform the procedures to carry out the flight. The guidance modes indicate procedures of the UAV, the guidance modes including lateral flight modes and vertical flight modes, that are subject to rules defined by the ANSP for travel through the airspace system under instrument flight rules (IFR), and the lateral flight modes and the vertical flight modes are separate and independent from one another.