publication . Article . 2020

Toward intelligent continuous assistance

Umbrico, Alessandro; Cortellessa, Gabriella; Orlandini, Andrea; Cesta, Amedeo;
Open Access
  • Published: 17 May 2020
  • Publisher: Zenodo
Technology supported assistance is a research area dedicated to support both older adults and, at some level, their caregivers in a variety of situations and contexts. A number of projects doing detailed evaluation both with robots and/or ICT-based intelligent devices have identified as open challenges the need to guarantee both continuity and variability of service according to context interpretation. This paper starts from the willingness to study how both continuity and variability can be pursued by leveraging and integrating results from research areas like artificial intelligence (AI), cognitive systems, psychology and sensor networks. Some of these technological skills are needed for example by an assistive robot and still represent open challenges in AI. This paper presents a medium term research initiative aiming at synthesizing an enhanced (intelligent) control architecture for assistive robots that take advantage from the continuous flow of information provided by a sensor network. The paper presents two main results: (a) starting from the analysis of requirements coming from the real world, it envisages a conceptual cognitive architecture highlighting the functional requirements and the key capabilities characterizing an “ideal” intelligent assistive robot; (b) it presents a prototype of a testbed architecture called KOaLa (Knowledge-based cOntinuous Loop) which integrates sensor data representation, knowledge reasoning and decision making capabilities showing its novelty in a realistic scenario.
Persistent Identifiers
free text keywords: General Computer Science, Context (language use), Cognitive architecture, Testbed, Service (systems architecture), Computational intelligence, Functional requirement, Human–computer interaction, Wireless sensor network, Robot, Computer science
Funded by
Safe and effective HumAn-Robot coopEration toWards a better cOmpetiveness on cuRrent automation lacK manufacturing processes.
  • Funder: European Commission (EC)
  • Project Code: 820807
  • Funding stream: H2020 | RIA
Validated by funder
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