RT Journal Article
T1 Probability and Common-Sense: Tandem Towards Robust Robotic Object Recognition in Ambient Assisted Living
A1 Ruiz-Sarmiento, José Raúl
A1 Galindo-Andrades, Cipriano
A1 González-Jiménez, Antonio Javier
K1 Robots autónomos
AB The suitable operation of mobile robots when providing Ambient Assisted Living (AAL) services calls for robust object recognition capabilities. Probabilistic Graphical Models (PGMs) have become the de-facto choice in recognition systems aiming to e ciently exploit contextual relations among objects, also dealing with the uncertainty inherent to the robot workspace. However, these models can perform in an inco herent way when operating in a long-term fashion out of the laboratory, e.g. while recognizing objects in peculiar con gurations or belonging to new types. In this work we propose a recognition system that resorts to PGMs and common-sense knowledge, represented in the form of an ontology, to detect those inconsistencies and learn from them. The utilization of the ontology carries additional advantages, e.g. the possibility to verbalize the robot's knowledge. A primary demonstration of the system capabilities has been carried out with very promising results.
YR 2016
FD 2016
LK http://hdl.handle.net/10630/12026
UL http://hdl.handle.net/10630/12026
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026