Peter Ondruska

According to our database, Peter Ondruska authored at least 24 papers between 2014 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

SafetyNet: Safe Planning for Real-World Self-Driving Vehicles Using Machine-Learned Policies.

Matt Vitelli, Yan Chang, Yawei Ye, Ana Ferreira, Maciej Wolczyk, Blazej Osinski, Moritz Niendorf, Hugo Grimmett, Qiangui Huang, Ashesh Jain, Peter Ondruska

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

2021

DriverGym: Democratising Reinforcement Learning for Autonomous Driving.

Parth Kothari, Christian Perone, Luca Bergamini, Alexandre Alahi, Peter Ondruska

CoRR, 2021

SafetyNet: Safe planning for real-world self-driving vehicles using machine-learned policies.

Matt Vitelli, Yan Chang, Yawei Ye, Maciej Wolczyk, Blazej Osinski, Moritz Niendorf, Hugo Grimmett, Qiangui Huang, Ashesh Jain, Peter Ondruska

CoRR, 2021

Autonomy 2.0: Why is self-driving always 5 years away?

Ashesh Jain, Luca Del Pero, Hugo Grimmett, Peter Ondruska

CoRR, 2021

What data do we need for training an AV motion planner?

Long Chen, Lukas Platinsky, Stefanie Speichert, Blazej Osinski, Oliver Scheel, Yawei Ye, Hugo Grimmett, Luca Del Pero, Peter Ondruska

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

SimNet: Learning Reactive Self-driving Simulations from Real-world Observations.

Luca Bergamini, Yawei Ye, Oliver Scheel, Long Chen, Chih Hu, Luca Del Pero, Blazej Osinski, Hugo Grimmett, Peter Ondruska

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients.

Oliver Scheel, Luca Bergamini, Maciej Wolczyk, Blazej Osinski, Peter Ondruska

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

One Thousand and One Hours: Self-driving Motion Prediction Dataset.

John Houston, Guido Zuidhof, Luca Bergamini, Yawei Ye, Ashesh Jain, Sammy Omari, Vladimir Iglovikov, Peter Ondruska

CoRR, 2020

Collaborative Augmented Reality on Smartphones via Life-long City-scale Maps.

Lukas Platinsky, Michal Szabados, Filip Hlasek, Ross Hemsley, Luca Del Pero, Andrej Pancik, Bryan Baum, Hugo Grimmett, Peter Ondruska

Proceedings of the 2020 IEEE International Symposium on Mixed and Augmented Reality, 2020

One Thousand and One Hours: Self-driving Motion Prediction Dataset.

John Houston, Guido Zuidhof, Luca Bergamini, Yawei Ye, Long Chen, Ashesh Jain, Sammy Omari, Vladimir Iglovikov, Peter Ondruska

Proceedings of the 4th Conference on Robot Learning, 2020

2018

Deep tracking in the wild: End-to-end tracking using recurrent neural networks.

Julie Dequaire, Peter Ondruska, Dushyant Rao, Dominic Zeng Wang, Ingmar Posner

Int. J. Robotics Res., 2018

Predicting trajectories of vehicles using large-scale motion priors.

M. S. Suraj, Hugo Grimmett, Lukas Platinsky, Peter Ondruska

Proceedings of the 2018 IEEE Intelligent Vehicles Symposium, 2018

Visual Vehicle Tracking Through Noise and Occlusions Using Crowd-Sourced Maps.

M. S. Suraj, Hugo Grimmett, Lukas Platinsky, Peter Ondruska

Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

VALUE: Large Scale Voting-Based Automatic Labelling for Urban Environments.

Giacomo Dabisias, Emanuele Ruffaldi, Hugo Grimmett, Peter Ondruska

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

2017

Large-scale cost function learning for path planning using deep inverse reinforcement learning.

Markus Wulfmeier, Dushyant Rao, Dominic Zeng Wang, Peter Ondruska, Ingmar Posner

Int. J. Robotics Res., 2017

2016

End-to-End Tracking and Semantic Segmentation Using Recurrent Neural Networks.

Peter Ondruska, Julie Dequaire, Dominic Zeng Wang, Ingmar Posner

CoRR, 2016

Deep Tracking on the Move: Learning to Track the World from a Moving Vehicle using Recurrent Neural Networks.

Julie Dequaire, Dushyant Rao, Peter Ondruska, Dominic Zeng Wang, Ingmar Posner

CoRR, 2016

Ask Me Anything: Dynamic Memory Networks for Natural Language Processing.

Ankit Kumar, Ozan Irsoy, Peter Ondruska, Mohit Iyyer, James Bradbury, Ishaan Gulrajani, Victor Zhong, Romain Paulus, Richard Socher

Proceedings of the 33nd International Conference on Machine Learning, 2016

Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks.

Peter Ondruska, Ingmar Posner

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

MobileFusion: Real-Time Volumetric Surface Reconstruction and Dense Tracking on Mobile Phones.

Peter Ondruska, Pushmeet Kohli, Shahram Izadi

IEEE Trans. Vis. Comput. Graph., 2015

Deep Inverse Reinforcement Learning.

Markus Wulfmeier, Peter Ondruska, Ingmar Posner

CoRR, 2015

Scheduled perception for energy-efficient path following.

Peter Ondruska, Corina Gurau, Letizia Marchegiani, Chi Hay Tong, Ingmar Posner

Proceedings of the IEEE International Conference on Robotics and Automation, 2015

2014

Probabilistic attainability maps: Efficiently predicting driver-specific electric vehicle range.

Peter Ondruska, Ingmar Posner

Proceedings of the 2014 IEEE Intelligent Vehicles Symposium Proceedings, 2014

The Route Not Taken: Driver-Centric Estimation of Electric Vehicle Range.

Peter Ondruska, Ingmar Posner

Proceedings of the Twenty-Fourth International Conference on Automated Planning and Scheduling, 2014