Fuzzy control-based real-time robust balance for a humanoid robot

Jun Wei Chang, Rong Jyue Wang, Che Han Chang, Hao Gong Chou, Wen June Wang

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

This paper studies and implements a real-time robust balance control for a humanoid robot under three environment disturbances which are an external thrust, an inclinable platform, and a see-saw. More precisely to say, the robot with robust control can resist an external thrust, stand on a two-axis inclinable platform, or walk on a see-saw successfully. The main feature of the robot is that it has a waist joint which has three degrees of freedom. With the aids of the proposed fuzzy controllers, the robot can change the posture of the body nimbly by adjusting the waist joint and two ankle joints to strengthen the stabilization capacity. The sensory system of the robot includes eight force sensors and one inertial measurement unit sensor in order to measure the center of pressure and the slant angle of the robot’s body. According to the measured data from the sensors and by imitating human reflex actions, the proposed fuzzy controllers perform real-time balance control for the robot under three environment disturbances. According to the experiment results, the stability of the robot is increased at least 32.2 and 61.7% under the first two environment disturbances, respectively. In addition, the robot walking on a see-saw has a success rate of about 95%.

Original languageEnglish
Pages (from-to)1288-1303
Number of pages16
JournalAdvanced Robotics
Volume30
Issue number19
DOIs
StatePublished - 1 Oct 2016

Keywords

  • balance control
  • fuzzy controller
  • Humanoid robot
  • sensor feedback

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