Human and environmental feature-driven neural network for path-constrained robot navigation using deep reinforcement learning

This paper introduces a neural network model designed for autonomous navigation in complex environments. It combines DRL methodologies to capture critical environmental features in the neural network. These features encompass data about the robot, humans, static obstacles, and path constraints. The...

ver descrição completa

Detalhes bibliográficos

Principais autores:	Nabih Pico, Estrella Montero, Alisher Amirbek, Eugene Auh, Jeongmin Jeon, Manuel S. Alvarez-Alvarado, Babar Jamil, Redhwan Algabri, Hyungpil Moon
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Elsevier 2025-04-01
Colecção:	Engineering Science and Technology, an International Journal
Assuntos:	Autonomous robot navigation Reinforcement learning Path constraint Motion and path planning
Acesso em linha:	http://www.sciencedirect.com/science/article/pii/S2215098625000485
Tags:	Adicionar Tag Sem tags, seja o primeiro a adicionar uma tag!