Acquiring grasp strategies for a multifingered robot hand using evolutionary algorithms

Chiaki Hirayama, Toshiya Watanabe, Shinji Kawabata, Masanori Suganuma, Tomoharu Nagao

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

1 Citation (Scopus)

Abstract

In recent years, significant research has been conducted on grasp planning for multifingered robot hands. These studies have focused on determining how to obtain suitable grasps from among an infinite number of candidate grasps. This domain's goal is a successful application to unknown environments through the adoption of the extracted grasps. Under difficult conditions, such as grasping a target object that is adjacent to other objects, manipulating robot hands by indicating grasping points has been insufficient. Instead, grasp strategies that construct movements using each finger's joint servo controls and robot hand movements should be used. In addition, it is necessary to automatically acquire various grasp strategies to apply to unknown environments. In this paper, we propose a method that automatically obtains grasp strategies using a real-coded genetic algorithm (RCGA), which is an evolutionary algorithm. This method derives grasp strategies by optimizing combinations and structures that consist of simple finger joint servo controls and robot hand movements. By applying our method to several objects on a simulator, we collected various grasp strategies capable of handling difficult conditions.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1597-1602
Number of pages6
ISBN (Electronic)9781538616451
DOIs
Publication statusPublished - 2017 Nov 27
Externally publishedYes
Event2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 - Banff, Canada
Duration: 2017 Oct 52017 Oct 8

Publication series

Name2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
Volume2017-January

Conference

Conference2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
CountryCanada
CityBanff
Period17/10/517/10/8

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Control and Optimization

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