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Sensors 2018, 18(2), 634; https://doi.org/10.3390/s18020634

Active Prior Tactile Knowledge Transfer for Learning Tactual Properties of New Objects

Institute for Cognitive Systems (ICS), Technische Universität München, Arcisstrasse 21, 80333 München, Germany
Mohsen Kaboli and Di Feng contributed equally to this work.
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Received: 1 November 2017 / Revised: 14 February 2018 / Accepted: 16 February 2018 / Published: 21 February 2018
(This article belongs to the Special Issue Tactile Sensors and Sensing)
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Abstract

Reusing the tactile knowledge of some previously-explored objects (prior objects) helps us to easily recognize the tactual properties of new objects. In this paper, we enable a robotic arm equipped with multi-modal artificial skin, like humans, to actively transfer the prior tactile exploratory action experiences when it learns the detailed physical properties of new objects. These experiences, or prior tactile knowledge, are built by the feature observations that the robot perceives from multiple sensory modalities, when it applies the pressing, sliding, and static contact movements on objects with different action parameters. We call our method Active Prior Tactile Knowledge Transfer (APTKT), and systematically evaluated its performance by several experiments. Results show that the robot improved the discrimination accuracy by around 10 % when it used only one training sample with the feature observations of prior objects. By further incorporating the predictions from the observation models of prior objects as auxiliary features, our method improved the discrimination accuracy by over 20 % . The results also show that the proposed method is robust against transferring irrelevant prior tactile knowledge (negative knowledge transfer). View Full-Text
Keywords: tactile sensing; artificial robotic skin; active tactile object perception; active tactile object learning; active tactile transfer learning tactile sensing; artificial robotic skin; active tactile object perception; active tactile object learning; active tactile transfer learning
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Feng, D.; Kaboli, M.; Cheng, G. Active Prior Tactile Knowledge Transfer for Learning Tactual Properties of New Objects. Sensors 2018, 18, 634.

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