| Deep learning quadcopter control via risk-aware active learning O Andersson, M Wzorek, P Doherty Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 40 | 2017 |
| Model-predictive control with stochastic collision avoidance using bayesian policy optimization O Andersson, M Wzorek, P Rudol, P Doherty 2016 IEEE International Conference on Robotics and Automation (ICRA), 4597-4604, 2016 | 20 | 2016 |
| Receding-horizon lattice-based motion planning with dynamic obstacle avoidance O Andersson, O Ljungqvist, M Tiger, D Axehill, F Heintz 2018 IEEE Conference on Decision and Control (CDC), 4467-4474, 2018 | 15 | 2018 |
| Model-based reinforcement learning in continuous environments using real-time constrained optimization O Andersson, F Heintz, P Doherty Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 12 | 2015 |
| Deep RL for autonomous robots: limitations and safety challenges O Andersson, P Doherty Proceedings of the European Symposium on Neural Networks (ESANN), 2019 | 1 | 2019 |
| Learning to Make Safe Real-Time Decisions Under Uncertainty for Autonomous Robots O Andersson Linköping University, 2020 | | 2020 |
| Real-Time Robotic Search using Hierarchical Spatial Point Processes O Andersson, P Sidén, J Dahlin, P Doherty, M Villani Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial …, 2019 | | 2019 |
| Toward Robust Deep RL via Better Benchmarks: Identifying Neglected Problem Dimensions O Andersson, P Doherty ICML'18 Workshop on Reproducible Machine Learning, 2018 | | 2018 |
Fredrik HeintzAssociate Professor of Computer Science, Linköping UniversityEmail confirmado em liu.se
