Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Hart, Fabian"'
Dynamic obstacle avoidance (DOA) is a fundamental challenge for any autonomous vehicle, independent of whether it operates in sea, air, or land. This paper proposes a two-step architecture for handling DOA tasks by combining supervised and reinforcem
Externí odkaz:
http://arxiv.org/abs/2311.16841
Autor:
Hart, Fabian, Okhrin, Ostap
In the field of autonomous robots, reinforcement learning (RL) is an increasingly used method to solve the task of dynamic obstacle avoidance for mobile robots, autonomous ships, and drones. A common practice to train those agents is to use a trainin
Externí odkaz:
http://arxiv.org/abs/2212.04123
While deep reinforcement learning (RL) has been increasingly applied in designing car-following models in the last years, this study aims at investigating the feasibility of RL-based vehicle-following for complex vehicle dynamics and strong environme
Externí odkaz:
http://arxiv.org/abs/2207.03257
We introduce a novel approach to dynamic obstacle avoidance based on Deep Reinforcement Learning by defining a traffic type independent environment with variable complexity. Filling a gap in the current literature, we thoroughly investigate the effec
Externí odkaz:
http://arxiv.org/abs/2112.12465
Publikováno v:
In Knowledge-Based Systems 25 October 2024 302
We propose and validate a novel car following model based on deep reinforcement learning. Our model is trained to maximize externally given reward functions for the free and car-following regimes rather than reproducing existing follower trajectories
Externí odkaz:
http://arxiv.org/abs/2109.14268
Publikováno v:
In Transportation Research Part C February 2024 159
Autor:
Hart, Fabian, Okhrin, Ostap
Publikováno v:
In Neurocomputing 1 February 2024 568
Publikováno v:
In Ocean Engineering 1 August 2023 281
Publikováno v:
In IFAC PapersOnLine 2019 52(8):233-238