GPT-4off: On-Board Traversability Probability Estimation for Off-Road Driving via GPT Knowledge Distillation

GPT-4off: On-Board Traversability Probability Estimation for Off-Road Driving via GPT Knowledge Distillation

This paper proposes a framework for predicting traversability probability in off-road environments by distilling knowledge from large language models (LLMs) such as GPT-4o into lightweight models. The GPT-4off approach utilizes GPT-generated data to train a compact model capable of real-time operati...

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Bibliographic Details
Main Authors: Nahyeong Kim, Seongkyu Choi, Sun Choi, Yejun Lee, Youngjae Cheong, Jhonghyun An
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Applied Sciences
Subjects:
GPT-4o
unmanned ground vehicle (UGV)
self-driving
knowledge distillation
off-road driving
deep learning
Online Access:https://www.mdpi.com/2076-3417/15/4/2130
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