Data-driven-based Stable Object Grasping for a Triple-fingered Under-actuated Robotic Hand

Ha Thang Long Doan, Kenji Tahara

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

3 Citations (Scopus)

Abstract

This paper proposes a data-driven-based stable object grasping method to grasp and realize object force/torque equilibrium for a triple-fingered under-actuated robotic system. Controlling the fingertip force of an under-actuated hand for precision grasp has been a challenging task in the robotic field due to the high nonlinearity of the under-actuated system as well as the inaccuracy in model-based controllers. By attaching a force sensor to the suitable location inside the robotic hand, necessary information for stable grasping, which is the detection of contact between fingertip and object and the magnitude of the fingertip force, is obtained using the proposed data-driven methods on internal sensor data in real-time. The obtained information is then used as feedback for the stable grasp controller to realize grasped object force/torque equilibrium.

Original languageEnglish
Title of host publication2023 IEEE/SICE International Symposium on System Integration, SII 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350398687
DOIs
Publication statusPublished - 2023
Event2023 IEEE/SICE International Symposium on System Integration, SII 2023 - Atlanta, United States
Duration: Jan 17 2023Jan 20 2023

Publication series

Name2023 IEEE/SICE International Symposium on System Integration, SII 2023

Conference

Conference2023 IEEE/SICE International Symposium on System Integration, SII 2023
Country/TerritoryUnited States
CityAtlanta
Period1/17/231/20/23

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computational Mechanics
  • Control and Optimization
  • Modelling and Simulation
  • Surgery
  • Instrumentation

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