Proprioceptive Visual Tracking of a Humanoid Robot Head Motion

This paper addresses the problem of measuring a humanoid robot head motion by fusing inertial and visual data. In this work, a model of a humanoid robot head, including a camera and inertial sensors, is moved on the tip of an industrial robot which is used as ground truth for angular position and velocity. Visual features are extracted from the camera images and used to calculate angular displacement and velocity of the camera, which is fused with angular velocities from a gyroscope and fed into a Kalman Filter. The results are quite interesting for two different scenarios and with very distinct illumination conditions. Additionally, errors are introduced artificially into the data to emulate situations of noisy sensors, and the system still performs very well.