With the increasing affordability of robot technologies and the reduction in size and weight of autonomous systems, the deployment of autonomous robotic systems on construction sites has gained significant attention. One major challenge faced by these systems is the accurate mapping and localization within an environment that constantly evolves on a daily basis. This computational problem, known as simultaneous localization and mapping (SLAM), has garnered substantial interest, leading to the proposal of various algorithms in recent years. This paper aims to provide a comprehensive overview of the SLAM algorithms by presenting the necessary background information, discussing the challenges involved in general, examining common approaches, and highlighting recent developments. Furthermore, the specific considerations related to deploying SLAM in construction environments are addressed. In order to provide practical insights into the advantages and use cases of state-of-the-art SLAM algorithms, a rigorous evaluation is conducted within a construction environment

中文翻译：

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建筑机器人应用的同步定位与建图 (SLAM) 回顾

随着机器人技术的可承受性不断提高以及自主系统尺寸和重量的减小，自主机器人系统在建筑工地上的部署受到了广泛关注。这些系统面临的一项主要挑战是在每天不断变化的环境中进行准确的地图绘制和定位。这种计算问题被称为同时定位和建图（SLAM），引起了人们的广泛兴趣，导致近年来提出了各种算法。本文旨在通过提供必要的背景信息、讨论一般涉及的挑战、检查常见方法并强调最新发展来全面概述 SLAM 算法。此外，还讨论了与在施工环境中部署 SLAM 相关的具体考虑因素。为了提供对最先进 SLAM 算法的优势和用例的实际见解，在施工环境中进行了严格的评估