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Low-Cost Sensor Integration for Robust Grasping with Flexible Robotic Fingers

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Advances and Trends in Artificial Intelligence. From Theory to Practice (IEA/AIE 2019)


Flexible gripping mechanisms are advantageous for robots when dealing with dynamic environments due to their compliance. However, a major obstacle to using commercially-available flexible fingers is the lack of appropriate feedback sensors. In this paper, we propose a novel integration of flexible fingers with commercial off-the-shelf proximity sensors. This integrated system enables us to perform non-interfering measurements of even minor deformations in the flexible fingers and consequently deduce information about grasped objects without the need of advanced fabrication methods. Our experiments have demonstrated that the sensor is capable of robustly detecting grasps on most test objects with an accuracy of 100% without false positives by relying on simple, yet powerful signal processing and can detect deformations of less than 0.03 mm. In addition, the sensor detects objects that are slipping through the flexible fingers.

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Correspondence to Sven Schneider .

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Kulkarni, P., Schneider, S., Ploeger, P.G. (2019). Low-Cost Sensor Integration for Robust Grasping with Flexible Robotic Fingers. In: Wotawa, F., Friedrich, G., Pill, I., Koitz-Hristov, R., Ali, M. (eds) Advances and Trends in Artificial Intelligence. From Theory to Practice. IEA/AIE 2019. Lecture Notes in Computer Science(), vol 11606. Springer, Cham.

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22998-6

  • Online ISBN: 978-3-030-22999-3

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