The interest in dynamic vision sensor (DVS)-powered unmanned aerial vehicles (UAV) is raising, especially due to the microsecond-level reaction time of the bio-inspired event sensor, which increases robustness and reduces latency of the perception tasks compared to a RGB camera. This work presents ColibriUAV, a UAV platform with both frame-based and event-based cameras interfaces for efficient perception and near-sensor processing. The proposed platform is designed around Kraken, a novel low-power RISC-V System on Chip with two hardware accelerators targeting spiking neural networks and deep ternary neural networks.Kraken is capable of efficiently processing both event data from a DVS camera and frame data from an RGB camera. A key feature of Kraken is its integrated, dedicated interface with a DVS camera. This paper benchmarks the end-to-end latency and power efficiency of the neuromorphic and event-based UAV subsystem, demonstrating state-of-the-art event data with a throughput of 7200 frames of events per second and a power consumption of 10.7 \si{\milli\watt}, which is over 6.6 times faster and a hundred times less power-consuming than the widely-used data reading approach through the USB interface. The overall sensing and processing power consumption is below 50 mW, achieving latency in the milliseconds range, making the platform suitable for low-latency autonomous nano-drones as well.

翻译：人们对动态视觉传感器驱动的无人机的兴趣日益增长，尤其是因为这种仿生事件传感器的微秒级反应时间，与RGB相机相比，提高了感知任务的鲁棒性并降低了延迟。本文介绍了ColibriUAV，一种同时配备帧相机和事件相机接口的无人机平台，用于高效感知和近传感器处理。该平台基于Kraken设计，Kraken是一种新型低功耗RISC-V系统级芯片，包含两个分别用于尖峰神经网络和深度三元神经网络的硬件加速器。Kraken能够高效处理来自DVS相机的事件数据和来自RGB相机的帧数据。其关键特性是集成了与DVS相机专用的接口。本文对神经形态和事件驱动的无人机子系统的端到端延迟和能效进行了基准测试，展示了事件数据的吞吐量达到每秒7200帧事件，功耗为10.7毫瓦，比广泛使用的通过USB接口读取数据的方法快6.6倍以上，且功耗低百倍。整个传感和处理功耗低于50毫瓦，延迟在毫秒级别，使该平台也适用于低延迟的自主纳米无人机。