This paper presents the DLR Laser Stripe Profiler as a component of the DLR multisensory Hand-Guided Device for 3D modeling. After modeling the reconstruction process, we propose a novel method for laser plane self-calibration based on the assessment of the deformations the miscalibration leads to. In addition, the requirement for absence of optical filtering implies the development of a robust stripe segmentation algorithm. Experiments demonstrate the validity and applicability of the approaches.

This article presents a novel gaze control strategy for obstacle avoidance in the context of vision guided humanoid walking. The generic strategy is based on the maximization of the predicted visual information. For information/uncertainty management a new hybrid formulation of an extended Kalman filter is employed. The performance resulting from this view direction control scheme shows the dependence of the intelligent gazing behavior on the pre-planned local path.

This article deals with specific aspects concerning the visual perception process of a humanoid walking machine. An active vision system provides the information about the environment necessary for autonomous goal-oriented locomotion. Due to errors in each stage of the perception process, ideal environment reconstruction is not possible. By modeling these errors, stochastic components can be compensated using a hybrid extended Kalman filter approach with an alternating reference frame, thus reflecting the discontinuous character of biped walking.. The perception results improved by filtering can be used for the autonomous locomotion of the robot. Experiments with the walking machine BARt-UH demonstrate the validity of our approach.

Goal-oriented vision-guided biped locomotion requires a high degree of coordination between perception and walking. How to establish this coordination remains a fundamental and rarely studied problem in legged robotics. Some of our investigations into this field are outlined in this article by presenting recent results in vision-guided biped locomotion. The guidance and control approaches developed are experimentally validated on the biped robot BARt-UH. It is shown how perception techniques are employed in closed-loop for step sequence adaptation and locomotion control of a walking machine.

This article deals with the information management for active gaze control in the context of vision-guided humanoid walking. The proposed biologically inspired predictive gaze control strategy is based on the maximization of visual information. The quantification of the information requires a stochastic model of both, the robot and perception system. The information/uncertainty management, i.e. relationships between the system, state estimation and the active measurements, employs a coupled (considering cross-covariances) hybrid (reflecting the discontinuous character of biped walking) extended (copes with nonlinear systems) Kalman filter approach.