Aerial Vehicle Autonomy PCB Layout for Low-Latency Localization
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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 ability to operate autonomously in urban environments.
Innovation Solution
A single circuit board with integrated processor devices and sensor assemblies, including GNSS, APNT, and RADAR, directly connected via conductive tracks, digitizes sensor data for real-time autonomy operations, reducing data copies and enabling triple redundant localization techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If sensor assemblies are connected via traditional high-bandwidth data buses, then data transfer capability is improved, but weight, size, and power consumption increase
Solution Approach 1:
The patent integrates the processor device and sensor assemblies onto a single circuit board, merging previously separate components into a unified architecture. This consolidation eliminates the need for heavy external cabling and intermediate data bus infrastructure, directly reducing weight while maintaining full data transfer capability through direct conductive connections on the board trace layer.
Solution Approach 2:
The circuit board itself serves as an intermediary substrate that provides both mechanical support and electrical connectivity between sensor assemblies and the processor device. By using the circuit board's integrated trace layer as the data transmission medium instead of traditional high-bandwidth data buses, the system achieves efficient data transfer with minimal weight penalty.
2Measurement precision
If multiple redundant circuit boards are used for triple redundant localization, then localization accuracy is improved, but device complexity increases
Solution Approach 1:
The system divides the autonomy computing function into three separate but identical circuit board modules, each capable of independent localization processing. This segmentation enables triple redundancy where each board can independently determine vehicle location using sensor data, and the system can vote or select among the three results to achieve high localization accuracy while maintaining manageable complexity through modular design.
Solution Approach 2:
The patent changes the architectural parameter from a single complex centralized processing unit to multiple simpler distributed processing units. By distributing the localization function across three independent circuit boards, the system achieves redundancy and improved accuracy while each individual board remains relatively simple in design, making the overall system easier to manufacture and maintain.
3Speed
If sensor data is digitized and processed in real-time on the circuit board, then processing speed is improved, but power consumption increases
Solution Approach 1:
The circuit board performs preliminary digitization and processing of sensor data immediately at the source before the data leaves the board. By converting analog sensor signals to digital format and performing initial processing operations right at the circuit board level, the system eliminates data transfer latency and enables real-time processing, while the distributed architecture allows power management across multiple independent modules.
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.