1 research outputs found
Online Adaptation for Humanoids Walking On Uncertain Surfaces
In this paper, an online adaptation algorithm for bipedal walking on uneven
surfaces with height uncertainty is proposed. In order to generate walking
patterns on flat terrains, the trajectories in the task space are planned to
satisfy the dynamic balance and slippage avoidance constraints, and also to
guarantee smooth landing of the swing foot. To ensure smooth landing of the
swing foot on surfaces with height uncertainty, the preplanned trajectories in
the task space should be adapted. The proposed adaptation algorithm consists of
two stages. In the first stage, once the swing foot reaches its maximum height,
the supervisory control is initiated until the touch is detected. After the
detection, the trajectories in the task space are modified to guarantee smooth
landing. In the second stage, this modification is preserved during the Double
Support Phase (DSP), and released in the next Single Support Phase (SSP).
Effectiveness of the proposed online adaptation algorithm is experimentally
verified through realization of the walking patterns on the SURENA III humanoid
robot, designed and fabricated at CAST. The walking is tested on a surface with
various flat obstacles, where the swing foot is prone to either land on the
ground soon or late