UAV Flight Path Risk Assessment Using 3D Depth Maps
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Solution Overview
Problem
Current UAV systems lack the ability to predictively assess and mitigate risks in flight paths based on real-time environmental data, particularly in complex geographical locations with varying object presence and accuracy.
Innovation Solution
A system that utilizes a three-dimensional representation of a user-selected location derived from depth maps from previous flights to determine predicted risk for UAV flight paths, incorporating object existence accuracies and risk parameters to generate notifications and adjust flight controls accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If preconfigured flight control settings are used for UAVs, then ease of operation is improved, but adaptability to different geographical locations and objects deteriorates
Solution Approach 1:
The system performs preliminary actions by pre-mapping geographical locations and building three-dimensional representations with object databases before UAV flights. This advance preparation enables the UAV to access pre-analyzed spatial information and object data during flight, resolving the contradiction between ease of operation and adaptability by having location-specific knowledge ready beforehand
Solution Approach 2:
The system implements feedback by continuously comparing the UAV's actual flight path and sensor data against the pre-established three-dimensional representation and object database. This feedback loop allows the UAV to adjust its flight control settings dynamically based on real-time conditions while maintaining ease of operation through automated adjustments
2Reliability
If three-dimensional representations with object databases are implemented, then reliability of flight path safety is improved, but device complexity increases
Solution Approach 1:
The system introduces an intermediary component - a server or ground station - that handles the complex tasks of building, storing, and managing three-dimensional representations and object databases. This intermediary absorbs the computational complexity, allowing the UAV itself to remain relatively simple while still benefiting from high-reliability spatial awareness through queries to the external database
Solution Approach 2:
The system creates a detailed three-dimensional copy or digital twin of the physical environment, including objects and their spatial relationships. This virtual representation serves as a reference model that enhances flight safety by allowing the UAV to plan and adjust its path based on the copied environment, reducing the need for complex real-time sensing and processing on the UAV itself
Data Source
AI summary
This disclosure relates to systems and methods for determining predicted risk for a flight path of an unmanned aerial vehicle. A previously stored three-dimensional representation of a user-selected location may be obtained. The three-dimensional representation may be derived from depth maps of the user-selected location generated during previous unmanned aerial vehicle flights. The three-dimensional representation may reflect a presence of objects and object existence accuracies for the individual objects. The object existence accuracies for the individual objects may provide information about accuracy of existence of the individual objects within the user-selected location. A user-created flight path may be obtained for a future unmanned aerial flight within the three-dimensional representation of the user-selected location. Predicted risk may be determined for individual portions of the user-created flight path based upon the three-dimensional representation of the user-selected location.