Towards flexible assistive robots using artificial intelligence

New generations of robotic systems capable of taking care of human-level tasks are becoming more and more desirable especially if considering the lack of human support in health-care assistance for the elderly. Assistive Robotics is a growing research field that is also applied to support both older adults and caregivers in a variety of situations and contexts. It leverages and integrates results from different research areas like e.g., Artificial Intelligence (AI), Cognitive Systems, Psychology and of course Robotics. Concerning AI, many of the technological skills that assistive robots could benefit of to achieve their objectives represent important challenges for that field. Some of the most relevant are the capability of monitoring and understanding information coming from the environment, the capability of interacting with humans in a flexible and human-compliant way, the capability of proactively performing supporting tasks inside the environment and also the capability of personalizing both interactions and services according to the specific needs of the assisted person. Thus, there are many techniques of AI that must be "integrated in a loop" to realize a needed set of advanced capabilities. This paper presents a research initiative which aims at realizing an enhanced (cognitive) control architecture to endow autonomous and socially interacting robots with a number of such advanced functionalities. Specifically, the paper presents an initial version of the envisaged control architecture, called KOaLa (Knowledge-based cOntinuous Loop) which integrates sensor data representation, knowledge reasoning and decision making functionalities.