Learning to stabilize the head of a quadrupedal robot with an artificial vestibular system

Abstract

During quadrupedal robot locomotion, there is pitch, yaw, and roll of the head and body due to the stepping. The head motion adversely affects visual sensors embedded in the robot's head. Mammals stabilize the head using a vestibulocollic reflex that detects linear and rotational acceleration. In this paper we describe the use of a machine learning algorithm that utilizes signals from an artificial vestibular system that has been embedded in the robot's head. Our approach can rapidly learn to compensate for the head movements that appear when no stabilization mechanism is present. The stabilization using a Sony Aibo robot occurs in only a few gait cycles.