Bipedal robotic walking control derived from analysis of human locomotion

Meng, Lin and Macleod, Catherine A. and Porr, Bernd and Gollee, Henrik (2018) Bipedal robotic walking control derived from analysis of human locomotion. Biological Cybernetics. ISSN 0340-1200 (https://doi.org/10.1007/s00422-018-0750-5)

[thumbnail of Meng-etal-BC-2018-Bipedal-robotic-walking-control-derived-from-analysis-of-human-locomotion]
Preview
Text. Filename: Meng_etal_BC_2018_Bipedal_robotic_walking_control_derived_from_analysis_of_human_locomotion.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo

Download (1MB)| Preview

Abstract

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.