Abstract
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.
Abstract (translated)
同时定位与映射系统是实现便携式和机器人应用的关键推动力。在过去的几年里，Hilti SLAM挑战赛已经成功地基准测试了世界上一些最好的SLAM系统，取得了高精度的成果。然而，这些系统还有许多功能有待探索，例如在各种传感器套件之间的平台无关性以及多会话SLAM。这些因素间接地表明了在现实应用中的稳健性和易用性。目前还没有公开可用的数据集和基准组合，同时考虑了这些因素。Hilti SLAM挑战2023数据集和基准解决了这个问题。此外，我们提出了一个新型的二维标记设计，用于从机器人上安装的便携式激光雷达上观察到预先调查的点的位置，并估计其达到毫米级的准确性。挑战赛的结果表明，总体参与度增加，单会话SLAM系统越来越精确，在各种传感器套件上成功运行，但相对较少参与者完成多会话SLAM。
URL
https://arxiv.org/abs/2404.09765
