Flight Controller Pipeline Scheduling for Low-Latency Actuation
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Solution Overview
Problem
Existing flight controller systems face challenges in efficiently processing sensor data and generating control signals due to asynchronous data polling and actuation, which can lead to performance issues and latency in real-time operations.
Innovation Solution
A pipeline-based flight controller system is introduced, where modules execute in parallel or sequence, with a scheduler managing execution times to prioritize tasks and ensure preemption, allowing for synchronous data processing and actuation, reducing latency and jitter.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If asynchronous polling is used for sensor data and actuator control, then system simplicity is maintained, but real-time performance and latency are degraded
Solution Approach 1:
The controller is divided into multiple independent modules organized in a pipeline architecture, where each module handles specific tasks (sensor data acquisition, processing, actuator control). This segmentation enables parallel execution of modules while maintaining deterministic timing, thus improving real-time performance without proportionally increasing overall system complexity.
Solution Approach 2:
The system implements dynamic scheduling where module execution times and priorities can be adjusted based on operational requirements. High-priority tasks can preempt lower-priority ones, allowing the system to adapt to varying real-time demands while maintaining a structured modular framework.
2Speed
If high-priority tasks are executed frequently, then real-time responsiveness is improved, but lower-priority tasks may be delayed or starved
Solution Approach 1:
The pipeline architecture implements periodic execution cycles where high-priority modules execute at fixed intervals with guaranteed timing. Lower-priority modules are scheduled in between or after high-priority ones, ensuring both get executed regularly without starvation, thus maintaining overall productivity while ensuring fast response for critical tasks.
Solution Approach 2:
The modular pipeline design allows continuous processing where multiple modules execute in parallel or in rapid succession. While high-priority tasks run frequently, lower-priority tasks continue to execute in the gaps, ensuring that the system maintains continuous useful action across all task types without idle time.
Data Source
AI summary
A pipeline in a controller may be configured to interface between sensors and actuators. The pipeline may elements such as drivers, filters, a combine, estimators, controllers, a mixer, and actuator controllers. The drivers may receive sensor data and pre-process the received sensor data. The filters may filter the pre-processed sensor data to generate filtered sensor data. The combine may package the filtered sensor data to generate packaged sensor data. The estimators may determine estimates of a position of a vehicle based on the packaged sensor data. The controllers may generate control signals based on the determined estimates. The mixer may modify the generated control signals based on limitations of the vehicle. The actuator controllers may generate actuator control signals based on the modified control signals to drive the actuators.