Generating explanations for autonomous robots: a systematic review

[EN] Building trust between humans and robots has long interested the robotics community. Various studies have aimed to clarify the factors that influence the development of user trust. In Human-Robot Interaction (HRI) environments, a critical aspect of trust development is the robot’s ability to ma...

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Detalles Bibliográficos
Autores: Sobrín Hidalgo, David, Guerrero Higueras, Ángel Manuel, Matellán Olivera, Vicente
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:10612/24702
Acceso en línea:https://ieeexplore.ieee.org/document/10855405
https://hdl.handle.net/10612/24702
Access Level:acceso abierto
Palabra clave:Informática
Robótica
Explainability
eXplainable autonomous robot
human–robot interaction
Literature review
Robotics
Survey
Trustworthy
33 Ciencias Tecnológicas
Descripción
Sumario:[EN] Building trust between humans and robots has long interested the robotics community. Various studies have aimed to clarify the factors that influence the development of user trust. In Human-Robot Interaction (HRI) environments, a critical aspect of trust development is the robot’s ability to make its behavior understandable. The concept of an eXplainable Autonomous Robot (XAR) addresses this requirement. However, giving a robot self-explanatory abilities is a complex task. Robot behavior includes multiple skills and diverse subsystems. This complexity led to research into a wide range of methods for generating explanations about robot behavior. This paper presents a systematic literature review that analyzes existing strategies for generating explanations in robots and studies the current XAR trends. Results indicate promising advancements in explainability systems. However, these systems are still unable to fully cover the complex behavior of autonomous robots. Furthermore, we also identify a lack of consensus on the theoretical concept of explainability, and the need for a robust methodology to assess explainability methods and tools has been identified.