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GAP9Shield: A 150GOPS AI-capable Ultra-low Power Module for Vision and Ranging Applications on Nano-drones

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arxiv 2407.13706 v1 pith:GJ5XEJYH submitted 2024-06-27 cs.RO cs.CVeess.SP

classification cs.ROcs.CVeess.SP
keywords applicationsgap9gap9shieldmodulepowercapabilitiesdetectionhardware
verification ladder T0 review T1 audit T2 compute T3 formal

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The evolution of AI and digital signal processing technologies, combined with affordable energy-efficient processors, has propelled the development of both 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 5MP OV5647 camera for high-definition imaging, a WiFi-BLE NINA module, and a 5D VL53L1-based ranging subsystem, which enhances obstacle avoidance capabilities. In comparison with similarly targeted state-of-the-art systems, GAP9Shield provides a 20% higher sample rate (RGB images) while offering a 20% weight reduction. In this paper, we also highlight the energy efficiency and processing power capabilities of GAP9 for object detection (YOLO), localization, 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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Cited by 1 Pith paper

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  1. Efficient and Accurate Downfacing Visual Inertial Odometry

    cs.CV 2025-09 conditional novelty 5.0 of 10

    A downfacing VIO pipeline with rigid-body motion estimation, running ORB, SuperPoint, and PX4FLOW on a GAP9 RISC-V SoC, reduces indoor RMSE by 3.65x on average versus the original PX4FLOW.

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