Bipedal robotic walking control derived from analysis of human locomotion

Research output: Contribution to journalArticle

This paper presents a human-inspired approach to the design of bipedal robotic walking control, using information that appears to be intrinsic to human walking. We first investigated the correlation between ground contact information from the feet and leg muscle activity (EMG) in human walking. From this relationship filter functions were created which relate the sensory input to motor actions producing a minimal, nonlinear and robust robotic controller which incorporates hip, knee and ankle control. The developed control system was subsequently analysed by applying it to our bipedal robot "RunBot III", a minimalistic robotic walker designed without any central pattern generators (CPGs) or precise trajectory control. Our results demonstrated that this controller, which regards the function between the sensory input and motor output as a black box derived from human data, can generate stable robotic walking. This indicates that complex locomotion patterns can result from a simple model based on reflexes and supports the premise that human-inspired methods have the potential for use in the control of robotics or in the development of assistive devices for gait.
Original languageEnglish
JournalBiological Cybernetics
StateAccepted/In press - 9 Jan 2018

    Research areas

  • reflexive rhythmic generator, robotics, bipedal locomotion, limit cycle walking, biological inspiration, human walking

View graph of relations