3 papers
cs.RO2016
Watch This: Scalable Cost-Function Learning for Path Planning in Urban Environments
Markus Wulfmeier, Dominic Zeng Wang, Ingmar Posner
In this work, we present an approach to learn cost maps for driving in complex urban environments from a very large number of demonstrations of driving behaviour by human experts.…
cs.LG2016
End-to-End Tracking and Semantic Segmentation Using Recurrent Neural Networks
Peter Ondruska, Julie Dequaire, Dominic Zeng Wang +1
In this work we present a novel end-to-end framework for tracking and classifying a robot's surroundings in complex, dynamic and only partially observable real-world environments.…
cs.LG2016
Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks
Peter Ondruska, Ingmar Posner
This paper presents to the best of our knowledge the first end-to-end object tracking approach which directly maps from raw sensor input to object tracks in sensor space without re…