Paper Info
Title
A context-awareness model for activity recognition in robot-assisted scenarios.
Abstract
Context awareness in ambient assisted living programmes for the elderly is a cornerstone in the current scenario of noncustomized service robots distributed around the world. This research proposes a context-awareness system for a human-robot scene interpretation based on seven primary contexts and the American Occupational Therapy Association. The context-awareness system defined here proposes an inference mechanism for the activity recognition supported on hierarchical Bayesian networks. However, when the information from sensors increases, the computational cost associated also increases. Thus, an evaluation of different Bayesian network models is necessary for decreasing its impact over the robot performance. Two topological models have been modelled and tested using OpenMarkov application: a two-level approach of an input-observations layer and the activity recognition layer, and a three-layer model setting apart a primary contexts layer, the input-observations layer, and the activity recognition layer. The qualitative and quantitative results presented here show better performance in terms of memory and memory in a three-layer model. Besides, its effect on a hybrid architecture of a robotic platform is presented.
Year
DOI
Venue
2020
10.1111/exsy.12481
EXPERT SYSTEMS
Keywords
DocType
Volume
activity recognition,Bayesian network,context awareness,knowledge representation
Journal
37.0
Issue
ISSN
Citations 
2.0
0266-4720
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Francisco J. Rodríguez Lera11110.94
Francisco Martín Rico223.76
Ángel Manuel Guerrero Higueras300.34
Vicente Matellán Olivera400.34