This paper presents a novel algorithm for crack localisation and detection based on visual and tactile analysis via fibre-optics. A finger-shaped sensor based on fibre-optics is employed for the data acquisition to collect data for the analysis and the experiments. To detect the possible locations of cracks a camera is used to scan an environment while running an object detection algorithm. Once the crack is detected, a fully-connected graph is created from a skeletonised version of the crack. A minimum spanning tree is then employed for calculating the shortest path to explore the crack which is then used to develop the motion planner for the robotic manipulator. The motion planner divides the crack into multiple nodes which are then explored individually. Then, the manipulator starts the exploration and performs the tactile data classification to confirm if there is indeed a crack in that location or just a false positive from the vision algorithm. If a crack is detected, also the length, width, orientation and number of branches are calculated. This is repeated until all the nodes of the crack are explored. In order to validate the complete algorithm, various experiments are performed: comparison of exploration of cracks through full scan and motion planning algorithm, implementation of frequency-based features for crack classification and geometry analysis using a combination of vision and tactile data. From the results of the experiments, it is shown that the proposed algorithm is able to detect cracks and improve the results obtained from vision to correctly classify cracks and their geometry with minimal cost thanks to the motion planning algorithm.

本文提出了一种基于光纤视觉和触觉分析的裂纹定位和检测算法，采用基于光纤的手指形传感器进行数据采集和实验，结合视觉算法扫描环境来检测裂纹位置，并通过机器人探测器进行裂纹分析和分类，最终通过运动规划算法实现裂纹的精确定位和长度、宽度、角度等参数的计算和准确分类检测。

具备视觉和触觉感应的机器人表面探测，用于裂缝检测和表征