2 papers
cs.CV2020
Deep Unsupervised Common Representation Learning for LiDAR and Camera Data using Double Siamese Networks
Andreas Bühler, Niclas Vödisch, Mathias Bürki +1
Domain gaps of sensor modalities pose a challenge for the design of autonomous robots. Taking a step towards closing this gap, we propose two unsupervised training frameworks for f…
cs.RO2018
Redundant Perception and State Estimation for Reliable Autonomous Racing
Nikhil Bharadwaj Gosala, Andreas Bühler, Manish Prajapat +9
In autonomous racing, vehicles operate close to the limits of handling and a sensor failure can have critical consequences. To limit the impact of such failures, this paper present…