Single-Board Aerial Autonomy Architecture for Low-Latency Flight
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Solution Overview
Problem
Existing aerial vehicles face challenges in efficiently integrating autonomy systems due to high bandwidth requirements, weight, size, and power consumption, which hinder their deployment in densely populated urban environments.
Innovation Solution
A single circuit board architecture integrating processor devices, sensor assemblies, and memory for implementing autonomy systems, including GNSS, APNT, and radar, directly connected via conductive tracks, reducing data copying and enabling real-time processing for autonomous flight.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional multi-component autonomy systems are used in aerial vehicles, then functional capability is achieved, but weight, size, and power consumption increase significantly
Solution Approach 1:
The patent combines multiple autonomy system components (sensor assemblies, processor devices, memory devices, and control systems) into a single integrated circuit board. This merging eliminates the need for separate housing, mounting structures, and inter-component connections, thereby significantly reducing the overall weight of the autonomy system while maintaining full functional capability for aerial vehicle operation.
Solution Approach 2:
The integrated circuit board serves multiple functions simultaneously: it houses sensor assemblies for environmental perception, processor devices for real-time data processing and motion planning, memory devices for storing operational data, and control systems for actuator management. This multi-functionality consolidates what would traditionally require separate subsystems into a single lightweight component.
2Productivity
If data is transmitted between separate autonomy system components, then functional processing is achieved, but latency increases due to data copying requirements
Solution Approach 1:
By integrating sensor assemblies, processor devices, and memory devices onto a single circuit board with direct conductive connections, the patent eliminates intermediate data transmission interfaces and copying operations. Data flows directly between components through trace-level connections, reducing processing latency and improving real-time data handling capability for autonomous flight operations.
3Reliability
If multiple separate circuit boards are used for autonomy functions, then redundancy is achieved, but system complexity and manufacturing difficulty increase
Solution Approach 1:
The patent integrates redundant autonomy system functions within a single circuit board architecture. The circuit board is designed to accommodate multiple sensor assemblies, processor devices, and memory devices that work together to provide fault tolerance and redundancy. This approach maintains reliability through built-in redundancy while eliminating the complexity of coordinating multiple separate boards and their interconnections.
4Measurement precision
If comprehensive sensor assemblies and processing systems are integrated, then localization accuracy improves, but bandwidth requirements and system size increase
Solution Approach 1:
The patent consolidates multiple sensor assemblies (including GNSS, APNT, and radar) and their associated processing systems onto a single circuit board. This integration enables comprehensive localization capabilities through triple redundant techniques while minimizing the system footprint by eliminating separate housings, mounting structures, and inter-component spacing required in traditional distributed architectures.
Data Source
AI summary
Systems and methods for controlling aerial vehicles are provided. An aerial vehicle includes a single circuit board with a number of processor devices and a memory including instructions to perform autonomy operations. The autonomy operations include obtaining GNSS data from GNSS assemblies electrically connected to the processor devices, APNT data from APNT assemblies electrically connected to the processor devices, and radar data from the radar assemblies electrically connected to the processor devices. Each of the assemblies are disposed on the same circuit board that includes the number of processor devices. The processor devices determine a vehicle location based on the GNSS data, the APNT data, and the radar data, identify airborne objects based on the radar data, generate a motion plan based on the vehicle location and the identified objects, and initiate a motion of the aerial vehicle based on the vehicle location.