ロボットビジョンarXiv:2404.08785
圧力下でも：実環境における学習ベースのアナログゲージ読み取り
Under pressure: learning-based analog gauge reading in the wild
実世界のロボットシステムに展開可能な、解釈可能なアナログゲージ読み取りフレームワークを提案。ゲージの種類やスケール範囲の事前知識を必要とせず、単位を抽出し、相対誤差2%未満で読み取り可能。
著者: Maurits Reitsma, Julian Keller, Kenneth Blomqvist, Roland Siegwart
分類: cs.CV, cs.LG, cs.RO
原文アブストラクト
We propose an interpretable framework for reading analog gauges that is deployable on real world robotic systems. Our framework splits the reading task into distinct steps, such that we can detect potential failures at each step. Our system needs no prior knowledge of the type of gauge or the range of the scale and is able to extract the units used. We show that our gauge reading algorithm is able to extract readings with a relative reading error of less than 2%.
