A Robot Hand with Capacitive Tactile Sensor for Object Recognition using Support Vector Machine

Xiaofei Liu, Wuqiang Yang, Fan Meng, Tengchen Sun

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

Touch sensing is essential for humans to perceive objects. Tactile sensing is also important for robot hand manipulation as it provides information on surface properties and interactive forces at contact points between robot fingers and an object. This paper presents a robot hand grasping system equipped with a novel capacitive tactile sensor. The sensor is integrated with a high-precision digital-analog hybrid chip based on a novel R-SpiNNaker architecture. According to the tactile dataset obtained from this system, object recognition is performed by the support vector machine (SVM) algorithm. The results show that superior performance is achieved by SVM with kernel of radial basis function, with accuracy of 98.6%.
Original languageEnglish
Title of host publication2023 IEEE International Instrumentation and Measurement Technology Conference
Subtitle of host publicationI2MTC 2023 Conference Proceedings
PublisherIEEE
Number of pages6
ISBN (Electronic)9781665453837
ISBN (Print)9781665453844
DOIs
Publication statusPublished - 13 Jul 2023
Event2023 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) - Kuala Lumpur, Malaysia
Duration: 22 May 202325 May 2023

Publication series

NameIEEE International Instrumentation and Measurement Technology Conference
PublisherIEEE
ISSN (Print)2642-2069
ISSN (Electronic)2642-2077

Conference

Conference2023 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
Period22/05/2325/05/23

Keywords

  • tactile sensing
  • object recognition
  • support vector machine

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