Cognitive Architectures in Autonomous Robotics: A Systematic Review of Behavior Generation Approaches and Evaluation Strategies
[EN] Cognitive architectures are an essential component in the development of intelligent autonomous robots, enabling planning, learning, and adaptation to dynamic environments. This paper presents a systematic review of the literature focused on cognitive architectures applied to behavior generatio...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universidad de León |
| Repositorio: | BULERIA. Repositorio Institucional de la Universidad de León |
| OAI Identifier: | oai:buleria.unileon.es:10612/26548 |
| Acceso en línea: | https://hdl.handle.net/10612/26548 |
| Access Level: | acceso abierto |
| Palabra clave: | Ingenierías Cognitive robotics Autonomous robots Systematic review 1203.04 Inteligencia Artificial |
| Sumario: | [EN] Cognitive architectures are an essential component in the development of intelligent autonomous robots, enabling planning, learning, and adaptation to dynamic environments. This paper presents a systematic review of the literature focused on cognitive architectures applied to behavior generation in autonomous robotics. A structured search and selection process was conducted using multiple scientific databases, applying explicit inclusion, exclusion, and quality assessment criteria. From an initial set of 502 studies, 22 publications (2018–mid-2025) were selected for in-depth analysis. The review identifies a growing trend toward hybrid architectures that integrate symbolic reasoning with data-driven methods, such as neural networks and behavior trees. The types of architectures, tools used (such as symbolic planners, neural networks, and behavior trees), middleware employed (with a predominance of Robot Operating System), as well as the methods and metrics used in their evaluation, are analyzed. This review provides a detailed overview of the state of the art and highlights the technologies and approaches currently most widely used in the design of cognitive robotic systems. |
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