2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI)最新文献_第8页

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2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI) Pub Date : 2023-06-08 DOI: 10.1109/iwasi58316.2023.10164362

引用次数: 0

Session 7: Sensor for healthcare applications II 第7部分:医疗保健应用传感器2

2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI) Pub Date : 2023-06-08 DOI: 10.1109/iwasi58316.2023.10164297

引用次数: 0

ColibriUAV: An Ultra-Fast, Energy-Efficient Neuromorphic Edge Processing UAV-Platform with Event-Based and Frame-Based Cameras ColibriUAV:一种具有基于事件和帧的相机的超快速，节能的神经形态边缘处理无人机平台

2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI) Pub Date : 2023-05-27 DOI: 10.1109/IWASI58316.2023.10164354

Sizhen Bian, Lukas Schulthess, Georg Rutishauser, Alfio Di Mauro, L. Benini, M. Magno

{"title":"ColibriUAV: An Ultra-Fast, Energy-Efficient Neuromorphic Edge Processing UAV-Platform with Event-Based and Frame-Based Cameras","authors":"Sizhen Bian, Lukas Schulthess, Georg Rutishauser, Alfio Di Mauro, L. Benini, M. Magno","doi":"10.1109/IWASI58316.2023.10164354","DOIUrl":"https://doi.org/10.1109/IWASI58316.2023.10164354","url":null,"abstract":"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 mW, 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.","PeriodicalId":261827,"journal":{"name":"2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129959164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

A Fast and Accurate Optical Flow Camera for Resource-Constrained Edge Applications 一种用于资源受限边缘应用的快速精确光流相机

2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI) Pub Date : 2023-05-22 DOI: 10.1109/IWASI58316.2023.10164626

Jonas Kühne, M. Magno, L. Benini

{"title":"A Fast and Accurate Optical Flow Camera for Resource-Constrained Edge Applications","authors":"Jonas Kühne, M. Magno, L. Benini","doi":"10.1109/IWASI58316.2023.10164626","DOIUrl":"https://doi.org/10.1109/IWASI58316.2023.10164626","url":null,"abstract":"Oiptical Flow (OF) is the movement pattern of pixels or edges that is caused in a visual scene by the relative motion between an agent and a scene. OF is used in a wide range of computer vision algorithms and robotics applications. While the calculation of OF is a resource-demanding task in terms of computational load and memory footprint, it needs to be executed at low latency, especially in robotics applications. Therefore, OF estimation is today performed on powerful CPUs or GPUs to satisfy the stringent requirements in terms of execution speed for control and actuation. On-sensor hardware acceleration is a promising approach to enable low latency OF calculations and fast execution even on resource-constrained devices such as nano drones and AR/VR glasses and headsets. This paper analyzes the achievable accuracy, frame rate, and power consumption when using a novel optical flow sensor consisting of a global shutter camera with an Application Specific Integrated Circuit (ASIC) for optical flow computation. The paper characterizes the optical flow sensor in high frame-rate, low-latency settings, with a frame rate of up to 88 fps at the full resolution of 1124 by 1364 pixels and up to 240 fps at a reduced camera resolution of 280 by 336, for both classical camera images and optical flow data.","PeriodicalId":261827,"journal":{"name":"2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125320378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1