Object Picking Using a Two-Fingered Gripper Measuring the Deformation and Slip Detection Based on a 3-Axis Tactile Sensing

Satoshi Funabashi, Yuta Kage, Hiroyuki Oka, Yoshihiro Sakamoto, Shigeki Sugano

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Object picking with two-fingered grippers is widely used in practice. However, the deformability and slipperiness of the target object still remain a challenge, and not resolving them might lead to breaking or dropping of the grasped objects. To prevent such instances, tactile sensing plays an important role because it can directly detect even the subtle changes that occur during grasping. Mechanoreceptors in the human skin detect such events by the change in the skin shape and/or vibration. Using a similar approach, a combined deformation and slip detection system using a distributed 3axis tactile information with various time-scales is proposed. Specifically, the tactile information includes the z-axis data, which denotes the deformation of the skin perpendicular to the finger's surface and the x-and y-axes, which measure deformations tangential to the surface. The perpendicular and tangential tactile information are used to determine the deformation and slip, respectively. The system is based on a multilayer perceptron (MLP) that outputs detection results from a 3-axis tactile information. Results showed that, the perpendicular and tangential tactile information with an appropriate timescale were effective for deformation and slip detection with over 89% and 95% recognition rates, respectively, measured for 40 different objects. Moreover, 195 out of 200 real-time untrained grasping states were successful detected. Finally, 10 untrained objects were successfully picked.

Original languageEnglish
Title of host publicationIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3888-3895
Number of pages8
ISBN (Electronic)9781665417143
DOIs
Publication statusPublished - 2021
Event2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021 - Prague, Czech Republic
Duration: 2021 Sep 272021 Oct 1

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
Country/TerritoryCzech Republic
CityPrague
Period21/9/2721/10/1

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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