Multi-UAV Fault Detection and Mitigation During Flight
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Unmanned aerial vehicles (UAVs) face challenges in identifying and responding to problem conditions such as battery failures and motor issues in real-time, especially during flights, as these conditions can be difficult for human operators to detect remotely.
Innovation Solution
A system comprising server computing devices that receive sensor feedback from UAVs, identify problem conditions, determine mitigation responses, and send instructions for the UAVs to maneuver and address these issues, allowing for remote monitoring and management of UAVs to prevent failures and ensure safe operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human operators remotely monitor UAVs during flight, then they can control the UAVs, but they cannot effectively identify problem conditions such as battery failures and motor issues in real-time
Solution Approach 1:
The UAV system performs self-diagnosis by automatically monitoring its own sensor data and identifying problem conditions. The computing device on the UAV analyzes sensor feedback from batteries, motors, and other components to detect issues without requiring external human intervention, enabling the system to serve its own monitoring needs
Solution Approach 2:
The system continuously collects sensor feedback from various UAV components and feeds this data back to the computing device for real-time analysis. This feedback loop enables automatic detection of problem conditions by comparing sensor readings against expected parameters and triggering appropriate responses
2Reliability
If the system automatically responds to problem conditions by determining mitigation responses, then flight safety improves, but the system complexity increases
Solution Approach 1:
The system pre-programs multiple mitigation responses to various problem conditions before flight operations begin. When a problem condition is detected, the computing device selects and executes the appropriate pre-determined response, such as initiating emergency landing procedures or adjusting flight parameters, eliminating the need for complex real-time decision-making algorithms
Solution Approach 2:
The automated response system is divided into separate functional modules: sensor data collection, problem condition identification, mitigation response determination, and response execution. Each module handles a specific aspect of the safety system, making the overall complex system more manageable and easier to implement through modular design
Data Source
AI summary
Aspects of the disclosure relate to identifying and responding to problem conditions for a fleet of aerial vehicles. This may include receiving at one or more processors of one or more server computing devices sensor feedback from an AV of the fleet. A problem condition may be identified using the sensor feedback. A mitigation response for the problem condition relating to a mission assigned to the aerial vehicle may be determined. The mitigation response may be sent to the AV in order to cause the aerial vehicle to maneuver according to the mitigation response and thereby automatically respond to the problem condition.