Task-Oriented and Situation-Dependent Gaze Control for Vision Guided Humanoid Walking

–This article presents various aspects of a gaze control scheme for visually guided humanoid robot navigation. The strategy is based on the maximization of the predicted visual information. For the information management a coupled hybrid Extended Kalman Filter is employed. Specific view direction control strategies for two concurrent objectives of different nature, obstacle avoidance and self-localization, have to be weighted and pursued in parallel. A combination of both shows the task dependence of the gazing strategy. The main goal of this work is to formalize and implement a decision strategy in order to achieve an intelligent task-oriented active vision system for a biped walking robot. It intends to explain the active vision decision making problem: Where to look next?, of an agent facing multiple and concurrent goals. The general approach rests upon the definition of a set of Utility Functions over the outcomes of the set of possible view directions. Next the various utility functions, i.e. Agents, representing different kinds of preference rankings over the predicted outcomes, are organized to solve the Action/Selection problem as a Society of Minds. Simulation results based on experimental experience demonstrate the applicability of the approach.

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