N. Ayari

A semantic approach for enhancing assistive services in ubiquitous robotics

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. Overview of the ubiquitous robotics and ambient intelligence.Hybrid model that bridges together the NKRL and the HARMS model.Context Aware modeling based on the upper ontologies of NKRL.Semantic Reasoning based Collective Intelligence in ubiquitous robotics.

A novel approach based on commonsense knowledge representation and reasoning in open world for intelligent ambient assisted living services

The next generation of ambient assisted living services will be based on eco-systems or organizations of intelligent artificial agents embodied in companion robots and smart objects. To provide, anywhere and anytime, smart assistance services to people, these agents need to be endowed with advanced knowledge representation, reasoning and communication capabilities. In this paper, we propose a distributed cognitive architecture allowing to integrate seamlessly the actors of the ambient system and an expressive model for commonsense knowledge representation and reasoning on events. This model allows a common description of the actors in an open world and a management of interactions with humans using natural language. A scenario dedicated to the cognitive assistance of frail people is implemented and analyzed for validation purposes of the proposed approach.

Semantic management of human-robot interaction in ambient intelligence environments using N-ary ontologies

In this paper, we present a semantic framework that is intended to enable natural interactions between ubiquitous robots and humans in Ambient Intelligence (AmI) environments. The main contribution of this paper is the extension of the core of the Narrative Knowledge Representation Language (NKRL) framework with semantic modules to allow on one hand, converting robot interactions into formal n-ary semantic annotations, and on the other hand, making semantic inferences for: (i) driving the human-robot dialogue, (ii) inferring the spatio-temporal context of the overall dialogue and (iii) mapping the inferred context with the actions that should be triggered in the AmI environment. A scenario dedicated to the monitoring and cognitive assistance of elderly people is implemented and discussed for validation purposes of the proposed framework.

Using Cognitive Ubiquitous Robots for Assisting Dependent People in Smart Spaces

In this chapter we discuss the necessity to move beyond built-in monotonic semantic web based reasoning-architectures for endowing ubiquitous robots with cognitive capabilities, which are strongly required in ambient assistive living, towards new architectures that combine different reasoning mechanisms to achieve better context awareness and adaptability in dynamic environments. We also present practical reasoning approaches that we have developed during the last decade for ambient intelligence and robotics applications. Finally, we discuss future directions that should be investigated to implement high-level cognitive capabilities that can be supported by cloud computing platforms as reasoning backend for robots and connected devices in smart spaces. These will enhance the human-environment interaction using robots, emergency prevention, management and rescue.