Peter Ondruska

According to our database1, Peter Ondruska authored at least 25 papers between 2014 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2022
SafetyNet: Safe Planning for Real-World Self-Driving Vehicles Using Machine-Learned Policies.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

2021
DriverGym: Democratising Reinforcement Learning for Autonomous Driving.
CoRR, 2021

SafetyNet: Safe planning for real-world self-driving vehicles using machine-learned policies.
CoRR, 2021

Autonomy 2.0: Why is self-driving always 5 years away?
CoRR, 2021

What data do we need for training an AV motion planner?
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

SimNet: Learning Reactive Self-driving Simulations from Real-world Observations.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients.
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.
CoRR, 2020

Collaborative Augmented Reality on Smartphones via Life-long City-scale Maps.
Proceedings of the 2020 IEEE International Symposium on Mixed and Augmented Reality, 2020

One Thousand and One Hours: Self-driving Motion Prediction Dataset.
Proceedings of the 4th Conference on Robot Learning, 2020

2018
Deep tracking in the wild: End-to-end tracking using recurrent neural networks.
Int. J. Robotics Res., 2018

Predicting trajectories of vehicles using large-scale motion priors.
Proceedings of the 2018 IEEE Intelligent Vehicles Symposium, 2018

Visual Vehicle Tracking Through Noise and Occlusions Using Crowd-Sourced Maps.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

VALUE: Large Scale Voting-Based Automatic Labelling for Urban Environments.
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.
Int. J. Robotics Res., 2017

2016
End-to-End Tracking and Semantic Segmentation Using Recurrent Neural Networks.
CoRR, 2016

Deep Tracking on the Move: Learning to Track the World from a Moving Vehicle using Recurrent Neural Networks.
CoRR, 2016

Ask Me Anything: Dynamic Memory Networks for Natural Language Processing.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
MobileFusion: Real-Time Volumetric Surface Reconstruction and Dense Tracking on Mobile Phones.
IEEE Trans. Vis. Comput. Graph., 2015

Deep Inverse Reinforcement Learning.
CoRR, 2015

Ask Me Anything: Dynamic Memory Networks for Natural Language Processing.
CoRR, 2015

Scheduled perception for energy-efficient path following.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

2014
Probabilistic attainability maps: Efficiently predicting driver-specific electric vehicle range.
Proceedings of the 2014 IEEE Intelligent Vehicles Symposium Proceedings, 2014

The Route Not Taken: Driver-Centric Estimation of Electric Vehicle Range.
Proceedings of the Twenty-Fourth International Conference on Automated Planning and Scheduling, 2014


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