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Autor:
Phan-Minh, Tung, Howington, Forbes, Chu, Ting-Sheng, Lee, Sang Uk, Tomov, Momchil S., Li, Nanxiang, Dicle, Caglayan, Findler, Samuel, Suarez-Ruiz, Francisco, Beaudoin, Robert, Yang, Bo, Omari, Sammy, Wolff, Eric M.
In this paper, we introduce the first learning-based planner to drive a car in dense, urban traffic using Inverse Reinforcement Learning (IRL). Our planner, DriveIRL, generates a diverse set of trajectory proposals, filters these trajectories with a
Externí odkaz:
http://arxiv.org/abs/2206.03004