The presentation will cover Xen Automotive. We will elaborate technical solutions for the identified gaps:
1. ARM architecture - support HW virtualization extensions for embedded systems
2. Stability requirements
3. RT Scheduler
4. Rich virtualized peripheral support (WiFi, Gfx, MM, USB, etc.)
5. Performance benchmarking
6. Security
Paul Durant, leader of the Windows PV Drivers effort in Xen Project, discusses the history, architecture, interfaces, and use of the drivers. Using the Windows PV Drivers yield higher performance for Windows VMs.
XPDS16: Xen Scalability Analysis - Weidong Han, Zhichao Huang & Wei Yang, HuaweiThe Linux Foundation
As CPU integrates more cores, server will have more and more cores. It requires hypervisor to have good scalability. This talk will introduce our analysis on many core scalability of Xen, and share some findings and lessons.
Many projects start out with the intention of staying single license FOSS projects. As your project grows, reality hits: some components or files may need to use different licenses than originally anticipated. There are many reasons why this can happen: you may need to interface with projects of another license, you may want to import code from other projects or your developers may not understand the subtleties of the licenses in use. Besides the obvious challenges of managing mixed license FOSS projects, such as license compatibility and tracking what licenses you use, you are running the risk of exposing your project to unintended consequences.
This talk will explore unintended consequences, risks and best practices using some examples from the recent history of the Xen Project. In particular we will cover:
1. Refactoring can lead to licensing changes: best practices and unintended consequences when importing code from elsewhere. Making code archeology easy from a licensing perspective and why it is important.
2. A worked example of a license change of a key component: process, pain points, their causes and how they could have been avoided
3. The perils of LGPL/GPL vX (or Later): the unintended consequences of not providing pre-defined copyright headers in your source base
We will conclude with a summary of lessons and best practices.
Subtitle: Reducing the OS burden while taking advantage of new hardware features
Xen is a hypervisor using a microkernel design that allows running multiple concurrent operating systems on the same hardware. One of the key features of Xen is that it is OS agnostic, meaning that any OS (with proper support) can be used as a host. Xen has a long history going back to the 90s when it was designed and the early 2000s when it was released. As a consequence of this, many of the assumptions and virtualization techniques backed into it are now superseeded by new hardware features, that make virtualization more transparent from an OS point of view.
This talk provides an overview on the different kind of guests supported by Xen and how these new hardware features are used in order to improve and evolve them. It also describes the design and implementation of a new guest type, called PVHv2, and how it can be used as a control domain (Dom0).
Also see: https://fosdem.org/2017/schedule/event/iaas_towahvm/
【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.
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