Mauricio Arias-Correa , Sebastián Robledo , Mateo Londoño , Johnatan Bañol , Carlos Madrigal-González , John R. Ballesteros , John W. Branch-Bedoya
{"title":"CYCLOPS:使用 RGB 摄像头和惯性测量单元(IMU)的自行车定向数据采集系统","authors":"Mauricio Arias-Correa , Sebastián Robledo , Mateo Londoño , Johnatan Bañol , Carlos Madrigal-González , John R. Ballesteros , John W. Branch-Bedoya","doi":"10.1016/j.ohx.2024.e00534","DOIUrl":null,"url":null,"abstract":"<div><p>This paper introduces CYCLOPS, an acquisition system developed to capture images and inertial measurement data of moving cyclists from a vehicle. The development of CYCLOPS addresses the need to acquire useful data for training machine learning models capable of predicting the motion intentions of cyclists on urban roads. Considering its application, it is a completely original development. The system consists of two devices. The first device is installed on the bicycle and is based on an electronic acquisition board comprising an inertial measurement unit (IMU), a microcontroller, and a transceiver for sending the cyclist’s acceleration and orientation data to a vehicle. The second device is installed on the vehicle and uses the same board architecture to acquire the vehicle’s accelerations and orientations, along with an RGB monocular camera. The data is stored in real-time in a laptop’s drive for subsequent analysis and manipulation. The hardware architecture is presented in detail, including the designs to install the devices, for IMUs configuration, and software installation on the laptop. All design and software files required to develop the proposed system are available for download at: <span>doi.org/10.17632/3yx5y8b7tm.1</span><svg><path></path></svg>, licensed under the Open-source license CC BY 4.0.</p></div>","PeriodicalId":37503,"journal":{"name":"HardwareX","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2468067224000282/pdfft?md5=eeda8ce057263719ceee17d5503caa9a&pid=1-s2.0-S2468067224000282-main.pdf","citationCount":"0","resultStr":"{\"title\":\"CYCLOPS: A cyclists’ orientation data acquisition system using RGB camera and inertial measurement units (IMU)\",\"authors\":\"Mauricio Arias-Correa , Sebastián Robledo , Mateo Londoño , Johnatan Bañol , Carlos Madrigal-González , John R. Ballesteros , John W. Branch-Bedoya\",\"doi\":\"10.1016/j.ohx.2024.e00534\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper introduces CYCLOPS, an acquisition system developed to capture images and inertial measurement data of moving cyclists from a vehicle. The development of CYCLOPS addresses the need to acquire useful data for training machine learning models capable of predicting the motion intentions of cyclists on urban roads. Considering its application, it is a completely original development. The system consists of two devices. The first device is installed on the bicycle and is based on an electronic acquisition board comprising an inertial measurement unit (IMU), a microcontroller, and a transceiver for sending the cyclist’s acceleration and orientation data to a vehicle. The second device is installed on the vehicle and uses the same board architecture to acquire the vehicle’s accelerations and orientations, along with an RGB monocular camera. The data is stored in real-time in a laptop’s drive for subsequent analysis and manipulation. The hardware architecture is presented in detail, including the designs to install the devices, for IMUs configuration, and software installation on the laptop. All design and software files required to develop the proposed system are available for download at: <span>doi.org/10.17632/3yx5y8b7tm.1</span><svg><path></path></svg>, licensed under the Open-source license CC BY 4.0.</p></div>\",\"PeriodicalId\":37503,\"journal\":{\"name\":\"HardwareX\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2468067224000282/pdfft?md5=eeda8ce057263719ceee17d5503caa9a&pid=1-s2.0-S2468067224000282-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"HardwareX\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468067224000282\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"HardwareX","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468067224000282","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
摘要
本文介绍的 CYCLOPS 是一种采集系统,用于从车辆上采集移动中的骑车人的图像和惯性测量数据。CYCLOPS 的开发是为了满足获取有用数据的需求,以训练能够预测城市道路上骑车人运动意图的机器学习模型。考虑到其应用,这是一项完全原创的开发。该系统由两个装置组成。第一个装置安装在自行车上,以电子采集板为基础,包括一个惯性测量单元(IMU)、一个微控制器和一个收发器,用于向车辆发送骑车人的加速度和方向数据。第二台设备安装在车辆上,使用相同的电路板结构来采集车辆的加速度和方向,同时还配有一个 RGB 单目摄像头。数据实时存储在笔记本电脑的驱动器中,以便进行后续分析和操作。详细介绍了硬件架构,包括安装设备的设计、IMU 配置以及笔记本电脑上的软件安装。开发该系统所需的所有设计和软件文件均可在以下网站下载:doi.org/10.17632/3yx5y8b7tm.1,采用 CC BY 4.0 开源许可证授权。
CYCLOPS: A cyclists’ orientation data acquisition system using RGB camera and inertial measurement units (IMU)
This paper introduces CYCLOPS, an acquisition system developed to capture images and inertial measurement data of moving cyclists from a vehicle. The development of CYCLOPS addresses the need to acquire useful data for training machine learning models capable of predicting the motion intentions of cyclists on urban roads. Considering its application, it is a completely original development. The system consists of two devices. The first device is installed on the bicycle and is based on an electronic acquisition board comprising an inertial measurement unit (IMU), a microcontroller, and a transceiver for sending the cyclist’s acceleration and orientation data to a vehicle. The second device is installed on the vehicle and uses the same board architecture to acquire the vehicle’s accelerations and orientations, along with an RGB monocular camera. The data is stored in real-time in a laptop’s drive for subsequent analysis and manipulation. The hardware architecture is presented in detail, including the designs to install the devices, for IMUs configuration, and software installation on the laptop. All design and software files required to develop the proposed system are available for download at: doi.org/10.17632/3yx5y8b7tm.1, licensed under the Open-source license CC BY 4.0.
HardwareXEngineering-Industrial and Manufacturing Engineering
CiteScore
4.10
自引率
18.20%
发文量
124
审稿时长
24 weeks
期刊介绍:
HardwareX is an open access journal established to promote free and open source designing, building and customizing of scientific infrastructure (hardware). HardwareX aims to recognize researchers for the time and effort in developing scientific infrastructure while providing end-users with sufficient information to replicate and validate the advances presented. HardwareX is open to input from all scientific, technological and medical disciplines. Scientific infrastructure will be interpreted in the broadest sense. Including hardware modifications to existing infrastructure, sensors and tools that perform measurements and other functions outside of the traditional lab setting (such as wearables, air/water quality sensors, and low cost alternatives to existing tools), and the creation of wholly new tools for either standard or novel laboratory tasks. Authors are encouraged to submit hardware developments that address all aspects of science, not only the final measurement, for example, enhancements in sample preparation and handling, user safety, and quality control. The use of distributed digital manufacturing strategies (e.g. 3-D printing) is encouraged. All designs must be submitted under an open hardware license.