Information management for gaze control in vision guided biped walking

Abstract
This article deals with the information management for active gaze control in the context of vision-guided humanoid walking. The proposed biologically in- spired predictive gaze control strategy is based on the maximization of visual information. The quan- tication of the information requires a stochastic model of both, the robot and perception system. The information/uncertainty management, i.e. relation- ship between system state estimation and the ac- tive measurements, employs a coupled (considering cross-covariances) hybrid (reecting the discontinu- ous character of biped walking) Extended (copes with nonlinear systems) Kalman Filter approach.

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