Continuous Modulation of Step Height and Length in Bipedal Walking, Combining Reflexes and a Central Pattern Generator

Deploying humanoid robots in complex and unstructured environments requires the development of efficient and adaptive locomotion controllers. Bio-inspiration holds promises in this perspective, since humans are known to have both an energy efficient gait, and the capacity to modulate it across several features like forward speed and step length and height. In this paper, we report the development of a bio-inspired controller for bipedal walking that can achieve controlled modulations of the step height and length over a large range. This controller builds upon our previous work where we combined both a Central Pattern Generator (CPG) and reflex-like modulations with a layer of virtual muscles providing human-like leg impedance. Here, we report first a sensitivity analysis that was performed to identify those among the many parameters of our controller that can actually modulate the step height and length. Then, we report experimental results illustrating such controlled modulations over a large parameter space.