PathGAN: Local path planning with attentive generative adversarial networks

PathGAN: Local path planning with attentive generative adversarial networks

For autonomous driving without high-definition maps, we present a model capable of generating multiple plausible paths from egocentric images for autonomous vehicles. Our generative model comprises two neural networks: feature extraction network (FEN) and path generation network (PGN). The FEN extra...

Full description

Bibliographic Details
Main Authors: Dooseop Choi, Seung-Jun Han, Kyoung-Wook Min, Jeongdan Choi
Format: Article
Language:English
Published: Electronics and Telecommunications Research Institute (ETRI) 2022-12-01
Series:ETRI Journal
Subjects:
autonomous driving dataset
deep learning
generative adversarial networks
imitation learning
path planning
Online Access:https://doi.org/10.4218/etrij.2021-0192

Internet

https://doi.org/10.4218/etrij.2021-0192

Similar Items