日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

SLAMarXiv:2108.01654

現代のオープンソースVisual SLAM手法の比較

Comparison of modern open-source visual SLAM approaches

シェア:XThreadsFacebookLINEはてブBluesky

複数のオープンソースVisual SLAM手法を精度・計算性能・堅牢性・耐故障性の観点で比較評価し、データセット比較と実用面の分析も行った論文。

著者: Dinar Sharafutdinov, Mark Griguletskii, Pavel Kopanev, Mikhail Kurenkov, Gonzalo Ferrer, Aleksey Burkov, Aleksei Gonnochenko, Dzmitry Tsetserukou

分類: cs.RO, cs.CV

原文アブストラクト

SLAM is one of the most fundamental areas of research in robotics and computer vision. State of the art solutions has advanced significantly in terms of accuracy and stability. Unfortunately, not all the approaches are available as open-source solutions and free to use. The results of some of them are difficult to reproduce, and there is a lack of comparison on common datasets. In our work, we make a comparative analysis of state of the art open-source methods. We assess the algorithms based on accuracy, computational performance, robustness, and fault tolerance. Moreover, we present a comparison of datasets as well as an analysis of algorithms from a practical point of view. The findings of the work raise several crucial questions for SLAM researchers.

関連論文

  1. 1Boston Dynamics、車輪付きAtlasの研究試作機を紹介研究・技術
  2. 2GXOとApptronik、Apolloの物流現場試験を拡大 最大1,000台の展開を構想量産・展開
  3. 3newmoとKDDIが資本業務提携 2028年に堺市で自動運転タクシー商用化目指す提携・買収
  4. 4NVIDIA、CoRLでGR00T 2とIsaac Lab 3.0を発表新製品・発表
  5. 5UC BerkeleyとNVIDIAの研究者、AIエージェントでロボット制御コードを仮想環境で改善研究・技術

PR・アフィリエイト広告

MINISFORUM(ミニPC)

MINISFORUM(ミニPC)の公式広告バナーMINISFORUM公式ストアを見る ↗
PR本紙発行元 EmplifAI