End-to-End AUV Local Motion Planning Method Based on Deep Reinforcement Learning

This study aims to solve the problems of sparse reward, single policy, and poor environmental adaptability in the local motion planning task of autonomous underwater vehicles (AUVs). We propose a two-layer deep deterministic policy gradient algorithm-based end-to-end perception–planning–execution me...

Descripció completa

Dades bibliogràfiques

Autors principals:	Xi Lyu, Yushan Sun, Lifeng Wang, Jiehui Tan, Liwen Zhang
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2023-09-01
Col·lecció:	Journal of Marine Science and Engineering
Matèries:	autonomous underwater vehicle (AUV) deep deterministic policy gradient (DDPG) deep reinforcement learning (DRL) local motion planning
Accés en línia:	https://www.mdpi.com/2077-1312/11/9/1796
Etiquetes:	Afegir etiqueta Sense etiquetes, Sigues el primer a etiquetar aquest registre!