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

翻译：同步定位与建图系统是手持设备与机器人应用中实现定位的关键使能技术。过去几年组织的 Hilti SLAM 挑战赛已成功地对全球一些最优秀的 SLAM 系统进行了高精度基准测试。然而，这些系统的更多能力仍有待探索，例如跨不同传感器套件的平台无关性以及多会话 SLAM。这些因素间接地作为系统在现实应用中鲁棒性和部署便捷性的指标。目前尚无公开可用的数据集与基准测试组合能够综合考虑这些因素。Hilti SLAM 挑战赛 2023 数据集与基准测试解决了这一问题。此外，我们提出了一种新颖的基准标记设计，用于地面上的预勘测点，使其能够被安装在机器人上的商用激光雷达观测到，并提出了一种算法以毫米级精度估计其位置。挑战赛结果显示，总体参与度有所提高，单会话 SLAM 系统精度日益提升，能够成功地在不同传感器套件上运行，但进行多会话 SLAM 的参与者相对较少。数据集网址：https://www.hilti-challenge.com/dataset-2023.html