Abstract
The evolution of AI and digital signal processing technologies, combined with affordable energy-efficient processors, has propelled the development of hardware and software for drone applications. Nano-drones, which fit into the palm of the hand, are suitable for indoor environments and safe for human interaction; however, they often fail to deliver the required performance for complex tasks due to the lack of hardware providing sufficient sensing and computing performance. Addressing this gap, we present the GAP9Shield, a nano-drone-compatible module powered by the GAP9, a 150GOPS-capable SoC. The system also includes a 5 MP camera for high-definition imaging, a Wi-Fi-BLE module, and a 5-directional laser-based ranging subsystem, enabling obstacle avoidance capabilities. Compared with similar state-of-the-art systems, GAP9Shield provides a 20% higher sample rate (RGB images) while offering 15% weight reduction. In this paper, we also highlight the energy efficiency and processing power capabilities of GAP9 for object detection using deep learning (YOLO), localization using a particle filter, and mapping, which can run within a power envelope of below 100 mW and at low latency (as 17 ms for object detection), highlighting the transformative potential of GAP9 for the new generation of nano-drone applications.
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The AI and ranger decks together weigh about 7 g and occupy 6480 mm\(^3\).
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Müller, H., Kartsch, V., Benini, L. (2024). GAP9Shield: A 150GOPS AI-Capable Ultra-low Power Module for Vision and Ranging Applications on Nano-drones. In: Secchi, C., Marconi, L. (eds) European Robotics Forum 2024. ERF 2024. Springer Proceedings in Advanced Robotics, vol 32. Springer, Cham. https://doi.org/10.1007/978-3-031-76424-0_52
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DOI: https://doi.org/10.1007/978-3-031-76424-0_52
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