Gaze Control for Goal-Oriented Humanoid Walking

Abstract

In this article a predictive task-dependent gaze control strategy for goal-oriented humanoid walking is presented. In the context of active vision systems we introduce an information theoretical approach for maximization of visual information. Based on two novel concepts, Information Content of a view situation and Incertitude, we present a method for selecting optimal subsequent view directions, thus contributing to an improved performance in typical semi-autonomous robot locomotion tasks. Simulations and experimental results dealing with the duality of concurrent tasks during locomotion, i.e. obstacle avoidance and self localization, demonstrate the applicability of our approach on humanoid walking machines.