Surface cracks in infrastructure can lead to significant deterioration and costly maintenance if not efficiently repaired. Manual repair methods are labor-intensive, time-consuming, and imprecise and thus difficult to scale to large areas. While advancements in robotic perception and manipulation have progressed autonomous crack repair, existing methods still face three key challenges: accurate localization of cracks within the robot's coordinate frame, (ii) adaptability to varying crack depths and widths, and (iii) validation of the repair process under realistic conditions. This paper presents an adaptive, autonomous system for surface crack detection and repair using robotics with advanced sensing technologies to enhance precision and safety for humans. The system uses an RGB-D camera for crack detection, a laser scanner for precise measurement, and an extruder and pump for material deposition. To address one of the key challenges, the laser scanner is used to enhance the crack coordinates for accurate localization. Furthermore, our approach demonstrates that an adaptive crack-filling method is more efficient and effective than a fixed-speed approach, with experimental results confirming both precision and consistency. In addition, to ensure real-world applicability and testing repeatability, we introduce a novel validation procedure using 3D-printed crack specimens that accurately simulate real-world conditions. This research contributes to the evolving field of human-robot interaction in construction by demonstrating how adaptive robotic systems can reduce the need for manual labor, improve safety, and enhance the efficiency of maintenance operations, ultimately paving the way for more sophisticated and integrated construction robotics.

翻译：基础设施中的表面裂缝若未得到有效修复，将导致显著劣化及高昂的维护成本。人工修复方法劳动密集、耗时且不精确，难以扩展至大面积区域。尽管机器人感知与操控技术的进步推动了自主裂缝修复的发展，现有方法仍面临三个关键挑战：(i) 在机器人坐标系内精确定位裂缝，(ii) 适应变化的裂缝深度与宽度，(iii) 在真实条件下验证修复过程。本文提出一种基于机器人技术的自适应自主表面裂缝检测与修复系统，该系统采用先进传感技术以提升精度与人员安全性。系统使用RGB-D相机进行裂缝检测，激光扫描仪进行精确测量，挤出器与泵进行材料沉积。针对关键挑战之一，激光扫描仪用于增强裂缝坐标以实现精确定位。此外，我们的方法证明自适应裂缝填充方法比固定速度方法更高效且有效，实验结果证实了其精度与一致性。同时，为确保实际适用性与测试可重复性，我们引入一种新颖的验证程序，使用3D打印裂缝试件精确模拟真实条件。本研究通过展示自适应机器人系统如何减少人工需求、提升安全性并提高维护作业效率，为建筑领域人机交互的不断发展做出贡献，最终为更复杂、集成化的建筑机器人技术铺平道路。