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

Robotic surface exploration with vision and tactile sensing for cracks detection and characterisation