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Motion planning and control are crucial components of robotics applications like automated driving. Here, spatio-temporal hard constraints like system dynamics and safety boundaries (e.g., obstacles) restrict the robot's motions. Direct methods from
Externí odkaz:
http://arxiv.org/abs/2210.11796
Autor:
Yazikova, Anastasiya A., Efremov, Aleksandr A., Poryvaev, Artem S., Polyukhov, Daniil M., Gjuzi, Eva, Oetzmann, Denise, Hoffmann, Frank, Fröba, Michael, Fedin, Matvey V.
Publikováno v:
In Journal of Hazardous Materials 5 October 2024 478
Offline reinforcement learning (RL) provides a framework for learning decision-making from offline data and therefore constitutes a promising approach for real-world applications as automated driving. Self-driving vehicles (SDV) learn a policy, which
Externí odkaz:
http://arxiv.org/abs/2111.11097