Implementing Tactile and Proximity Sensing for Crack Detection

Remote characterisation of the environment during physical robot-environment interaction is an important task commonly accomplished in telerobotics. This paper demonstrates how tactile and proximity sensing can be efficiently used to perform automatic crack detection. A custom-designed integrated tactile and proximity sensor is implemented. It measures the deformation of its body when interacting with the physical environment and distance to the environment’s objects with the help of fibre optics. This sensor was used to slide across different surfaces and the data recorded during the experiments was used to detect and classify cracks, bumps and undulations. The proposed method uses machine learning techniques (mean absolute value as feature and random forest as classifier) to detect cracks and determine their width.

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Bibtext Citation:

@inproceedings{palermo2020crack, title={Implementing Tactile and Proximity Sensing for Crack Detection}, author={Palermo, Francesca and Konstantinova, Jelizaveta and Althoefer, Kaspar and Poslad, Stefan and Farkhatdinov, Ildar}, booktitle={2020 IEEE International Conference on Robotics and Automation (ICRA)}, pages={}, year={2020}, organization={IEEE}}