Cooperative motion control of 2-DOF robot arms by recurrent neural network

Yingda Dai, Masami Konishi, Jun Imai, Tatsushi Nishi

Research output: Contribution to conferencePaperpeer-review


Recently Robotics has been applied in many fields. Robot designers have focused the applications that from the standardization factory, in which all kinds of industrial robots run repeatedly, to the social welfare field, where there is no standard but need higher safety. However, according to today's technology, the ability that robot can quickly enough to adapt a new environment is still worse by far than human. The intent of this paper is to show the control plan for two degrees of freedom (2-DOF) dexterous robot arms both of these two robot arms operate in operation under the realistic environment. This control system can be synthesized quickly by neural network algorithms.

Original languageEnglish
Number of pages6
Publication statusPublished - Dec 1 2005
EventSICE Annual Conference 2005 - Okayama, Japan
Duration: Aug 8 2005Aug 10 2005


OtherSICE Annual Conference 2005


  • Cooperation Control
  • Neural Network
  • Robot Arm
  • Self-learning

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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