Abstract
Tactile sensing has become crucial in robotic applications such as teleoperation, as it gives information about the object properties that cannot be perceived by other senses. In fact, it is essential that robots are equipped with advanced touch sensing in order to be aware of their surroundings and give a feedback to an operator. Such sensing systems are made of sensors and an elaboration unit that acquires tactile signals and process the data, retrieving information such as texture, hardness, and shape. In this paper, we propose a novel tactile sensing system made of flexible, high sensitive and high spatial resolution piezoelectric polyvinylidene fluoride‐trifluoroethylene P(VDF-TrFE) sensors, and a low power and low cost Interface Electronics (IE) that can acquire data from 32 channels simultaneously with a sampling frequency of 2KSamples/s. We validate the system acquiring data from three different objects to classify their hardness using an artificial neural network of one hidden layer with approximately 89% accuracy. The signal processing and the classifier will be hosted by the IE in the next future.
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Acknowledgment
The authors acknowledge partial financial support from TACTIle feedback enriched virtual interaction through virtual reality and beyond (TACTILITY) project: EU H2020, Topic ICT-25-2018-2020, RIA, Proposal ID 856718. The authors acknowledge the support of Prof. Fulvio Mastrogiovanni and Dr. Hossein Karami, DIBRIS, University of Genova, for making available the Baxter robot.
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Amin, Y., Gianoglio, C., Valle, M. (2023). A Novel Tactile Sensing System for Robotic Tactile Perception of Object Properties. In: Di Francia, G., Di Natale, C. (eds) Sensors and Microsystems. AISEM 2021. Lecture Notes in Electrical Engineering, vol 918. Springer, Cham. https://doi.org/10.1007/978-3-031-08136-1_28
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DOI: https://doi.org/10.1007/978-3-031-08136-1_28
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