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SLAMarXiv:2404.09765

Hilti SLAMチャレンジ2023:建設現場における多様なセンサ構成での単一・複数セッションSLAMのベンチマーク

Hilti SLAM Challenge 2023: Benchmarking Single + Multi-session SLAM across Sensor Constellations in Construction

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建設現場でのSLAM性能を評価する新データセットとベンチマークを提供し、異なるセンサ構成や複数セッションSLAMの課題に取り組んだ。また、LiDARで観測可能な新規マーカーとmm精度の位置推定アルゴリズムを提案した。

著者: Ashish Devadas Nair, Julien Kindle, Plamen Levchev, Davide Scaramuzza

分類: cs.RO, eess.IV

原文アブストラクト

Simultaneous Localization and Mapping systems are a key enabler for positioning in both handheld and robotic applications. The Hilti SLAM Challenges organized over the past years have been successful at benchmarking some of the world's best SLAM Systems with high accuracy. However, more capabilities of these systems are yet to be explored, such as platform agnosticism across varying sensor suites and multi-session SLAM. These factors indirectly serve as an indicator of robustness and ease of deployment in real-world applications. There exists no dataset plus benchmark combination publicly available, which considers these factors combined. The Hilti SLAM Challenge 2023 Dataset and Benchmark addresses this issue. Additionally, we propose a novel fiducial marker design for a pre-surveyed point on the ground to be observable from an off-the-shelf LiDAR mounted on a robot, and an algorithm to estimate its position at mm-level accuracy. Results from the challenge show an increase in overall participation, single-session SLAM systems getting increasingly accurate, successfully operating across varying sensor suites, but relatively few participants performing multi-session SLAM. Dataset URL: https://www.hilti-challenge.com/dataset-2023.html

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