Special Issue on Part 1 — New Advances of Humanoid Robotics (Humanoids 2018)
Guest Editors: Qiang Huang (Beijing Institute of Technology, China), Fumio Kanehiro (AIST, Japan), Tamim Asfour (Karlsruhe Institute of Technology, Germany), Abderrahmane Kheddar (CNRS-UM LIRMM, France) and Zhangguo Yu (Beijing Institute of Technology, China)

Abstract

This paper contributes toward the benchmarking of control architectures for bipedal robot locomotion. It considers architectures that are based on the Divergent Component of Motion (DCM) and composed of three main layers: trajectory optimization, simplified model control, and whole-body quadratic programming (QP) control layer. While the first two layers use simplified robot models, the whole-body QP control layer uses a complete robot model to produce either desired positions, velocities, or torques inputs at the joint-level. This paper then compares two implementations of the simplified model control layer, which are tested with position, velocity, and torque control modes for the whole-body QP control layer. In particular, both an instantaneous and a Receding Horizon controller are presented for the simplified model control layer. We show also that one of the proposed architectures allows the humanoid robot iCub to achieve a forward walking velocity of 0.3372m/s, which is the highest walking velocity achieved by the iCub robot.

Keywords:

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