Data Integrity Techniques: Aviation Best Practices for CRC & Checksum Error D...Philip Koopman
Author: Prof. Philip Koopman, Carnegie Mellon University
Abstract:
This talk includes both a tutorial and explanation of research results on the proper use of Cyclic Redundancy codes (CRCs) and checksums in an aviation context. More than 50 years since the invention of the CRC, the proper use of these error detection codes is still hampered by a combination of misleading folklore, sub-optimality of standard approaches, general inaccessibility of research results, and the occasional typographical error in key reference materials. However, recent work has been able to exhaustively explore the CRC design space and identify optimal selection criteria based on key system characteristics. This talk will covers the following areas: checksum and CRC theory with an emphasis on intuitive understanding rather than heavy math; why using a standard or widely used CRC can be suboptimal (or worse); how to pick a good checksum/CRC; the key parameters that affect the error detection capability of a checksum/CRC; CRC pitfalls illustrated via examples from Controller Area Network and ARINC-825; an example CRC selection process for achieving a required level of functional criticality; and a “seven deadly sins” list for CRC/checksum use. Some key research findings that are discussed include: a well-chosen CRC is usually dramatically better than a checksum for relatively little additional computational cost; you can usually do a lot better than “standard” CRC (especially CRC-32); Hamming Distance at the target payload length is the predominant selection criterion of interest; and it is important to avoid bit encoding approaches that undermine CRC effectiveness.
Bio:
Dr. Philip Koopman is a professor at Carnegie Mellon University, with research interests in the areas of software robustness, embedded networking, dependable embedded computer systems, and autonomous vehicle safety. Previously, he was a US Navy submarine officer, an embedded CPU architect for Harris Semiconductor, and an embedded system researcher at United Technologies. In addition to a variety of academic publications and two dozen patents, he has authored the book Better Embedded System Software based on lessons learned from more than a hundred design reviews of industry software. He has affiliations with both the Carnegie Mellon Electrical & Computer Engineering Department (ECE) and the National Robotics Engineering Center (NREC). He is a senior member of IEEE, senior member of the ACM, and a member of IFIP WG 10.4 on Dependable Computing and Fault Tolerance.
【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.
20. @twovs
pakeana05_08.pcap
For IPv6, the first address must be the IPv6 link-
local address associated with the virtual router.
(RFC5798#section-5.2.9) 20
