Anticipatory Driving for a Robot-Car Based on Supervised Learning

Authors:
Irene Markelić;Tomas Kulviĉius;Minija Tamosiunaite;Florentin Wörgötter
Affiliations:
Bernstein Center for Computational Neuroscience, University of Göttingen, Göttingen, Germany 37073;Bernstein Center for Computational Neuroscience, University of Göttingen, Göttingen, Germany 37073;Vytautas Magnus University, Kaunas, Lithuania;Bernstein Center for Computational Neuroscience, University of Göttingen, Göttingen, Germany 37073
Venue:
Anticipatory Behavior in Adaptive Learning Systems
Year:
2009

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Abstract

Prediction and Planning are essential elements of successful human driving, making them equally important for autonomously driving systems. Many approaches achieve planning based on built-in world-knowledge. However, we show how a learning-based system can be extended to planning, needing little a priori knowledge. A car-like robot is trained by a human driver by constructing a database, where look ahead sensory information is stored together with action sequences . From that we achieve a novel form of velocity control, based only on information in image coordinates. For steering we employ a two-level approach in which database information is combined with an additional reactive controller. The result is a trajectory planning robot running at real-time, issuing steering and velocity control commands in a human manner.