English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Open

Presents the pdf analysis as premium feature

PDF Analysis

Insights

Presents the summarisation as premium feature

Summarisation

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

To increase the autonomy of a vision guided walking robot, perception must be controlled such that the humanoid is provided with sufficient information about its environment. This article outlines a modular task-specific and situation-dependent gaze control scheme which selects an optimal view direction allowing the goal-oriented acquisition of the relevant information. The basic idea of the approach rests upon maximization of the predicted visual information content of a view situation. For information management, a hybrid Extended Kalman Filter is proposed considering the peculiarities of legged locomotion. Specific view direction evaluation strategies for obstacle avoidance and self-localization tasks are formulated. For dealing with these conflicting objectives a decision strategy for situation-dependent view direction selection based on Utility Theory is presented. Several references to related published work on simulative validation and real-world experiments with different robot platforms are given. The results demonstrate the relevance and practicality of the proposed gaze control approach in the framework of a system for vision-guided humanoid walking.

Gaze Control Strategy for Vision-Guided Humanoid Walking (Blickwinkelsteuerung für visuell geführtes humanoides Laufen)