RT info:eu-repo/semantics/article
T1 Towards explainability in robotics: A performance analysis of a cloud accountability system
A1 Rodríguez Lera, Francisco Javier
A1 González Santamarta, Miguel Ángel
A1 Guerrero Higueras, Ángel Manuel
A1 Martín Rico, Francisco
A1 Matellán Olivera, Vicente
A2 Ciencias de la Computacion e Inteligencia Artificial
K1 Ingeniería de sistemas
K1 Accountability
K1 Autonomous agents
K1 Explainability
K1 Traceability
AB [EN] Understanding why a robot's behaviour was triggered is a growing concern to get human-acceptable social robots. Every action, expected and unexpected, should be able to be explained and audited. The formal model proposed here deals with different information levels, from low-level data, such as sensors' data logging; to high-level data that provide an explanation of the robot's behaviour. This study examines the impact on the robot system of a custom log engine based on a custom ROS logging node and investigates pros and cons when used together with a NoSQL database locally and in a cloud environment. Results allow to characterize these alternatives and explore the best strategy for offering a fully log-based accountability engine that maximizes the mapping between robot behaviour and robot logs.
PB Wiley-Blackwell
SN 0266-4720
LK http://hdl.handle.net/10612/15388
UL http://hdl.handle.net/10612/15388
NO Rodríguez-Lera, F. J., González-Santamarta, M. Á., Guerrero-Higueras, Á. M., Martín-Rico, F., & Matellán-Olivera, V. (2022). Towards explainability in robotics: A performance analysis of a cloud accountability system. Expert Systems, 39(9). https://doi.org/10.1111/EXSY.13004
DS BULERIA. Repositorio Institucional de la Universidad de León
RD 04-may-2024