A Holistic Approach to Behavior Adaptation for Socially Assistive Robots
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A Holistic Approach to Behavior Adaptation for Socially Assistive Robots Alessandro Umbrico1
· Amedeo Cesta1
· Gabriella Cortellessa1
· Andrea Orlandini1
Accepted: 19 December 2019 © Springer Nature B.V. 2020
Abstract Socially assistive robotics aims at providing users with continuous support and personalized assistance, through appropriate social interactions. The design of robots capable of supporting people in heterogeneous tasks, raises several challenges among which the most relevant are the need to realise intelligent and continuous behaviours, robustness and flexibility of services and, furthermore, the ability to adapt to different contexts and needs. Artificial intelligence plays a key role in realizing cognitive capabilities like e.g., learning, context reasoning or planning that are highly needed in socially assistive robots. The integration of several of such capabilities is an open problem. This paper proposes a novel “cognitive approach” integrating ontology-based knowledge reasoning, automated planning and execution technologies. The core idea is to endow assistive robots with intelligent features in order to reason at different levels of abstraction, understand specific health-related needs and decide how to act in order to perform personalized assistive tasks. The paper presents such a cognitive approach pointing out the contribution of different knowledge contexts and perspectives, presents detailed functioning traces to show adaptation and personalization features, and finally discusses an experimental assessment proving the feasibility of the approach. Keywords Socially assistive robotics · Artificial intelligence · Knowledge representation and Reasoning · User profiling and personalization
1 Introduction Socially assistive robotics (SAR) is a rather new research area that aims at developing robots capable of assisting users through social rather than physical interaction [23,40]. The main goal of socially assistive robots is to provide continuous support by means of appropriate emotional, cognitive, and social cues to assistance for individuals. SAR systems employ hands-off interaction strategies to provide assistance in accordance with a particular assistive context and
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Gabriella Cortellessa [email protected] Alessandro Umbrico [email protected] Amedeo Cesta [email protected] Andrea Orlandini [email protected]
1
CNR – Italian National Research Council, ISTC – Institute of Cognitive Sciences and Technologies, Via S. Martino della Battaglia 44, 00185 Rome, Italy
to improve access to personalized care, training and rehabilitation to a wide variety of users, including elderly, in order to enhance their quality of life. An effective socially assistive robot should understand and interact with its environment, exhibit social behaviour, focus the attention on and communicate with the user, sustain engagement with the user, and achieve specific assistive goals. SAR systems are then usually deployed in a significant number of heterogeneous sit
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