NanoCockpit: Performance-optimized Application Framework for AI-based Autonomous Nanorobotics

TL;DR

NanoCockpit is a framework that enhances the performance and developer experience of AI-powered nano-drones by optimizing resource utilization and reducing latency in embedded systems.

Contribution

It introduces a software layer that enables time-optimal pipelining and multi-tasking on resource-constrained nano-drone MCUs, improving control performance.

Findings

Achieves zero overhead in task serialization, maximizing throughput.

Reduces mean position error by 30% in real-world tests.

Increases mission success rate from 40% to 100%.

Abstract

Autonomous nano-drones, powered by vision-based tiny machine learning (TinyML) models, are a novel technology gaining momentum thanks to their broad applicability and pushing scientific advancement on resource-limited embedded systems. Their small form factor, i.e., a few tens of grams, severely limits their onboard computational resources to sub-100mW microcontroller units (MCUs). The Bitcraze Crazyflie nano-drone is the de facto standard, offering a rich set of programmable MCUs for low-level control, multi-core processing, and radio transmission. However, roboticists very often underutilize these onboard precious resources due to the absence of a simple yet efficient software layer capable of time-optimal pipelining of multi-buffer image acquisition, multi-core computation, intra-MCUs data exchange, and Wi-Fi streaming, leading to sub-optimal control performances. Our NanoCockpit framework aims to fill this gap, increasing the throughput and minimizing the system's latency, while simplifying the developer experience through coroutine-based multi-tasking. In-field experiments on three real-world TinyML nanorobotics applications show our framework achieves ideal end-to-end latency, i.e. zero overhead due to serialized tasks, delivering quantifiable improvements in closed-loop control performance (-30% mean position error, mission success rate increased from 40% to 100%).