Driving Through Ghosts: Behavioral Cloning with False Positives

no code implementations • 29 Aug 2020 • Andreas Bühler, Adrien Gaidon, Andrei Cramariuc, Rares Ambrus, Guy Rosman, Wolfram Burgard

In this work, we propose a behavioral cloning approach that can safely leverage imperfect perception without being conservative.

Autonomous Driving

Deep Unsupervised Common Representation Learning for LiDAR and Camera Data using Double Siamese Networks

no code implementations • 3 Jan 2020 • Andreas Bühler, Niclas Vödisch, Mathias Bürki, Lukas Schaupp

Domain gaps of sensor modalities pose a challenge for the design of autonomous robots.

Representation Learning

AMZ Driverless: The Full Autonomous Racing System

4 code implementations • 13 May 2019 • Juraj Kabzan, Miguel de la Iglesia Valls, Victor Reijgwart, Hubertus Franciscus Cornelis Hendrikx, Claas Ehmke, Manish Prajapat, Andreas Bühler, Nikhil Gosala, Mehak Gupta, Ramya Sivanesan, Ankit Dhall, Eugenio Chisari, Napat Karnchanachari, Sonja Brits, Manuel Dangel, Inkyu Sa, Renaud Dubé, Abel Gawel, Mark Pfeiffer, Alexander Liniger, John Lygeros, Roland Siegwart

This paper presents the algorithms and system architecture of an autonomous racecar.

Robotics

Redundant Perception and State Estimation for Reliable Autonomous Racing

no code implementations • 26 Sep 2018 • Nikhil Bharadwaj Gosala, Andreas Bühler, Manish Prajapat, Claas Ehmke, Mehak Gupta, Ramya Sivanesan, Abel Gawel, Mark Pfeiffer, Mathias Bürki, Inkyu Sa, Renaud Dubé, Roland Siegwart

In autonomous racing, vehicles operate close to the limits of handling and a sensor failure can have critical consequences.