A Semantic Approach for Enhancing Assistive Services in ubiquitous robotics

N. Ayari 1 A. Chibani 1 Yacine Amirat 1 E. Matson 2
LISSI - Laboratoire Images, Signaux et Systèmes Intelligents
Abstract : The Ambient Intelligence (AmI) technologies have the potential to create intelligent environments with new generation of assistive services, enhanced with ubiquitous robots. These environments have the ability to be anticipatory, responsive and intelligent providers of assistive services anytime and anywhere. These services can assist frail persons effectively in their daily tasks. One of the main challenging research problems in assistive robotics is to endow ubiquitous robots with ability to pro-actively taking on some tasks to help humans in performing complex activities, by participating with them just as other humans do, in normal societies or organizations. In this paper, we propose a collective intelligence framework based on narrative reasoning and natural language processing. In the proposed approach, we propose a hybrid model that bridges together the Narrative Knowledge Representation Language (NKRL), from natural language processing field, and the HARMS (Humans, software Agents, Robots, Machines and Sensors) model, from multi-agent systems engineering field. This model is able to (i) drive the dialogues between humans, robots and smart devices, (ii) understand a complex situation, and (iii) trigger reactive actions, in the ubiquitous environment, according to given contexts. Two scenarios dedicated to the assistance of a frail person in a smart home equipped with a companion robot and smart objects are implemented and discussed for validation purposes of the proposed framework.
Liste complète des métadonnées

Contributor : Lab Lissi <>
Submitted on : Tuesday, June 13, 2017 - 4:23:33 PM
Last modification on : Friday, April 12, 2019 - 10:56:17 AM


  • HAL Id : hal-01538498, version 1



N. Ayari, A. Chibani, Yacine Amirat, E. Matson. A Semantic Approach for Enhancing Assistive Services in ubiquitous robotics. Robotics and Autonomous Systems, Elsevier, 2016, Part A, 75, pp.17-27. ⟨hal-01538498⟩



Record views