Aerial Detect and Avoid System Sensor Switching
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Solution Overview
Problem
Current detect and avoid systems for aerial vehicles are ineffective in adverse weather conditions and require significant maintenance, contributing to delays in aerial delivery operations and passenger transport, due to limitations in sensor capabilities and reliance on pre-loaded maps.
Innovation Solution
A system and method that includes a set of sensors coupled to an aerial vehicle to generate signals for detect and avoid functionality, transitioning between operation modes, and employing novel design features for efficient package handling and safety, with architecture for decision-making in various traffic and environmental conditions, including aerodynamic surfaces and thrust elements for improved flight performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vision systems are used for detect and avoid functionality, then detection capability is improved under good weather conditions, but reliability deteriorates under poor weather conditions
Solution Approach 1:
The patent implements a sensor suite that includes multiple types of sensors (vision systems, acoustic systems, radar systems, LIDAR) where each sensor type can operate effectively under different weather conditions. The system selects and switches between appropriate sensor types based on environmental conditions, ensuring reliable detection across varying weather scenarios.
Solution Approach 2:
The system dynamically changes operational parameters by switching between different sensor types and detection modes based on weather conditions. For example, transitioning from vision-based detection in clear weather to radar or acoustic detection in adverse weather, thereby maintaining detection reliability across different environmental parameters.
2Measurement precision
If acoustic systems are used for detect and avoid functionality, then detection capability is improved in certain conditions, but reliability deteriorates when environmental noise exceeds threshold
Solution Approach 1:
The system incorporates multiple sensor types including acoustic sensors, vision sensors, radar, and LIDAR. When acoustic noise exceeds thresholds, the system automatically switches to alternative sensor types that are not affected by acoustic interference, maintaining reliable obstacle detection across different environmental noise conditions.
3Reliability
If radar systems are added to improve detect and avoid capability, then reliability is improved, but weight of aerial vehicle increases
Solution Approach 1:
The system dynamically selects and activates sensor types based on operational requirements and environmental conditions rather than continuously operating all sensors. This dynamic approach allows the system to achieve reliable detection when needed while minimizing weight-related energy consumption and structural requirements by not permanently integrating heavy radar systems for all operations.
Solution Approach 2:
The patent implements a sensor suite with multiple detection technologies where not all sensors are always active or required. The system uses partial action by selecting only the necessary sensor types for current operational conditions, thereby achieving sufficient detection reliability without the full weight penalty of having all sensor types at maximum capability.
4Measurement precision
If pre-loaded maps are used for navigation and obstacle avoidance, then detection accuracy is improved, but device complexity increases due to memory requirements and maintenance
Solution Approach 1:
The patent replaces the mechanical approach of storing and processing large pre-loaded map databases with a sensor-based real-time detection system. Instead of relying on stored geographic information and complex path planning algorithms, the system uses multiple sensor types to directly detect and avoid obstacles in real-time, thereby reducing memory requirements and maintenance complexity while maintaining detection accuracy.
Data Source
AI summary
Embodiments of the invention(s) cover a method and system in which the system monitors outputs of a set of subsystems associated with a flying vehicle, wherein the flying vehicle comprises a set of fixed-wing operation modes and a set of vertical take-off and landing (VTOL) operation modes, and wherein the set of subsystems generate signals associated with an operational environment surrounding the flying vehicle; from said outputs of the set of subsystems, generating a risk assessment characterizing one or more potential hazards associated with the environment surrounding the flying vehicle; based upon the risk assessment, returning instructions for execution of a detect and avoid operation; and optionally, executing the detect and avoid operation.