A Systematic Literature Review of Decision-Making and Control Systems for Autonomous and Social Robots

Datos Bibliográficos

ID21199657
AutoresMarcos Maroto‐Gómez (0000-0001-9576-1731, Universidad Carlos III de Madrid, autor de correspondencia), Fernándo Alonso-Martín (0000-0003-3013-968X, Universidad Carlos III de Madrid), María Malfáz (0000-0003-2317-3329, Universidad Carlos III de Madrid), Álvaro Castro‐González (0000-0002-5189-0002, Universidad Carlos III de Madrid), José Carlos Castillo (0000-0003-0454-9466, Universidad Carlos III de Madrid), Miguel Á Salichs (0000-0002-0263-6606, Universidad Carlos III de Madrid)
Año2023
Volumen15
Número5
Páginas745-789
Fecha de publicación2023-05-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaInternational Journal of Social Robotics (JOURNAL)
Identificadores de la revistaISSN: 1875-4791 • E-ISSN: 1875-4805
EditorialSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s12369-023-00977-3
OpenAlexW4360986002
IdiomaEN
Citas recibidas5
Referencias citadas131

In the last years, considerable research has been carried out to develop robots that can improve our quality of life during tedious and challenging tasks. In these contexts, robots operating without human supervision open many possibilities to assist people in their daily activities. When autonomous robots collaborate with humans, social skills are necessary for adequate communication and cooperation. Considering these facts, endowing autonomous and social robots with decision-making and control models is critical for appropriately fulfiling their initial goals. This manuscript presents a systematic review of the evolution of decision-making systems and control architectures for autonomous and social robots in the last three decades. These architectures have been incorporating new methods based on biologically inspired models and Machine Learning to enhance these systems’ possibilities to developed societies. The review explores the most novel advances in each application area, comparing their most essential features. Additionally, we describe the current challenges of software architecture devoted to action selection, an analysis not provided in similar reviews of behavioural models for autonomous and social robots. Finally, we present the future directions that these systems can take in the future

Human–computer interaction · Robot · Robotics · AI in Service Interactions · Computer Science · Reinforcement Learning in Robotics · Social Robot Interaction and HRI · Artificial Intelligence