Easy-to-use IoT system created with Azure and EnOceanAtomu Hidaka
EnOcean is Energy Hervesting wireless system for IoT that is widely used worldwide. In this session, I will introduce an open source system that can register Azure IoT Hub devices with a single button on each EnOcean device. This system, which can be used easily with more than 70 sensors and Raspberry Pi in Japan, contributes to the easy spread of IoT.
Tips and tricks for Azure IoT system developmentAtomu Hidaka
Developing Azure Edge devices requires not only knowledge of devices and protocols, but also the various SDKs and tools that Azure provides. In this session, I will introduce small techniques such as IoT-Edge, IoT-SDK, and VS Code that make it easy to develop IoT Edge-side systems based on Raspberry Pi-based Azure IoT EnOceran gateway development examples.
This is a document that explains how to use the Azure IoT Central basic functions from a browser. This will allow beginners to take advantage of IoT Central.
Azure IoT Plug and Play, the overview and practiceAtomu Hidaka
Azure IoT Plug and Play is a new service for IoT announced at BUILD in May. In this session, I will explain the outline of this service, including the relationship with Azure Digital Twins, while comparing it with the protocols for IoT devices such as BLE, EnOcean and OPC UA that are already popular.
Through this session, listeners can learn about the newer trends in Azure IoT.
Easy-to-use IoT system created with Azure and EnOceanAtomu Hidaka
EnOcean is Energy Hervesting wireless system for IoT that is widely used worldwide. In this session, I will introduce an open source system that can register Azure IoT Hub devices with a single button on each EnOcean device. This system, which can be used easily with more than 70 sensors and Raspberry Pi in Japan, contributes to the easy spread of IoT.
Tips and tricks for Azure IoT system developmentAtomu Hidaka
Developing Azure Edge devices requires not only knowledge of devices and protocols, but also the various SDKs and tools that Azure provides. In this session, I will introduce small techniques such as IoT-Edge, IoT-SDK, and VS Code that make it easy to develop IoT Edge-side systems based on Raspberry Pi-based Azure IoT EnOceran gateway development examples.
This is a document that explains how to use the Azure IoT Central basic functions from a browser. This will allow beginners to take advantage of IoT Central.
Azure IoT Plug and Play, the overview and practiceAtomu Hidaka
Azure IoT Plug and Play is a new service for IoT announced at BUILD in May. In this session, I will explain the outline of this service, including the relationship with Azure Digital Twins, while comparing it with the protocols for IoT devices such as BLE, EnOcean and OPC UA that are already popular.
Through this session, listeners can learn about the newer trends in Azure IoT.
Microsoft MVP/Regional Director x Microsoft Japan Digital Days #MSDD2021Rie Moriguchi
2021年10月12日にDay 1を迎えた日本マイクロソフト株式会社主催カンファレンスMicrosoft Japan Digital Daysの開催に合わせて、カンファレンスに様々な形でご協力いただいたMicrosoft MVPおよびRegional Directorについて本資料にてご紹介しています。さらに、10名のMicrosoft MVP受賞者のオリジナル学習コレクションをご紹介しておりますので、皆さまの今後の学習にお役立てください。
【DLゼミ】XFeat: Accelerated Features for Lightweight Image Matchingharmonylab
公開URL:https://arxiv.org/pdf/2404.19174
出典:Guilherme Potje, Felipe Cadar, Andre Araujo, Renato Martins, Erickson R. ascimento: XFeat: Accelerated Features for Lightweight Image Matching, Proceedings of the 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023)
概要:リソース効率に優れた特徴点マッチングのための軽量なアーキテクチャ「XFeat(Accelerated Features)」を提案します。手法は、局所的な特徴点の検出、抽出、マッチングのための畳み込みニューラルネットワークの基本的な設計を再検討します。特に、リソースが限られたデバイス向けに迅速かつ堅牢なアルゴリズムが必要とされるため、解像度を可能な限り高く保ちながら、ネットワークのチャネル数を制限します。さらに、スパース下でのマッチングを選択できる設計となっており、ナビゲーションやARなどのアプリケーションに適しています。XFeatは、高速かつ同等以上の精度を実現し、一般的なラップトップのCPU上でリアルタイムで動作します。
セル生産方式におけるロボットの活用には様々な問題があるが,その一つとして 3 体以上の物体の組み立てが挙げられる.一般に,複数物体を同時に組み立てる際は,対象の部品をそれぞれロボットアームまたは治具でそれぞれ独立に保持することで組み立てを遂行すると考えられる.ただし,この方法ではロボットアームや治具を部品数と同じ数だけ必要とし,部品数が多いほどコスト面や設置スペースの関係で無駄が多くなる.この課題に対して音𣷓らは組み立て対象物に働く接触力等の解析により,治具等で固定されていない対象物が組み立て作業中に運動しにくい状態となる条件を求めた.すなわち,環境中の非把持対象物のロバスト性を考慮して,組み立て作業条件を検討している.本研究ではこの方策に基づいて,複数物体の組み立て作業を単腕マニピュレータで実行することを目的とする.このとき,対象物のロバスト性を考慮することで,仮組状態の複数物体を同時に扱う手法を提案する.作業対象としてパイプジョイントの組み立てを挙げ,簡易な道具を用いることで単腕マニピュレータで複数物体を同時に把持できることを示す.さらに,作業成功率の向上のために RGB-D カメラを用いた物体の位置検出に基づくロボット制御及び動作計画を実装する.
This paper discusses assembly operations using a single manipulator and a parallel gripper to simultaneously
grasp multiple objects and hold the group of temporarily assembled objects. Multiple robots and jigs generally operate
assembly tasks by constraining the target objects mechanically or geometrically to prevent them from moving. It is
necessary to analyze the physical interaction between the objects for such constraints to achieve the tasks with a single
gripper. In this paper, we focus on assembling pipe joints as an example and discuss constraining the motion of the
objects. Our demonstration shows that a simple tool can facilitate holding multiple objects with a single gripper.