Autonomous Critical Help by a Robotic Assistant in the Field of Cultural Heritage: A New Challenge for Evolving Human-Robot Interaction

Over the years, the purpose of cultural heritage (CH) sites (e.g., museums) has focused on providing personalized services to different users, with the main goal of adapting those services to the visitors’ personal traits, goals, and interests. In this work, we propose a computational cognitive model that provides an artificial agent (e.g., robot, virtual assistant) with the capability to personalize a museum visit to the goals and interests of the user that intends to visit the museum by taking into account the goals and interests of the museum curators that have designed the exhibition. In particular, we introduce and analyze a special type of help (critical help) that leads to a substantial change in the user’s request, with the objective of taking into account the needs that the same user cannot or has not been able to assess. The computational model has been implemented by exploiting the multi-agent oriented programming (MAOP) framework JaCaMo, which integrates three different multi-agent programming levels. We provide the results of a pilot study that we conducted in order to test the potential of the computational model. The experiment was conducted with 26 real participants that have interacted with the humanoid robot Nao, widely used in Human-Robot interaction (HRI) scenarios.

Human-robot interaction through adjustable social autonomy

Autonomy is crucial in cooperation. The complexity of HRI scenarios requires autonomous robots able to exploit their superhuman computations (based on DNN, Machine Learning techniques and Big Data) in a trustworthy way. Trustworthiness is not only a matter of accuracy, privacy or security, but it is becoming more and more a matter of adaptation to humans agency. As claimed by Falcone and Castelfranchi, autonomy means the possibility of dislaying or providing an unexpected behavior (including refusal) that departs from a requested (agreed upon or not) behavior. In this sense, the autonomy to decide how to adopt a task delegated by the user, with respect to her/his own real needs and goals, distinguishes intelligent and trustworthy robots from highly performing robots. This kind of smart help can be provided only by cognitive robots able to represent and ascribe mental states (beliefs, goals, intentions, desires etc.) to their interlocutors. The mental states attribution can be the result of complex reasoning mechanisms or can be fast and automatic, based on scripts, roles, categories or stereotypes typically exploited by humans every time they interact in everyday life. In all these cases, robots that build and use cognitive models of humans (that have a Theory of Mind of their interlocutors), have to operate also a meta-evaluation of their own predictive skills to build those models. Robots have to be endowed with the capability to self-trust their skills to interpret the interlocutors and the context, for producing smart and effective decisions towards humans. After exploring the main concepts that make collaboration between humans and robots trustworthy and effective, we present the first of a series of experiments draw for testing different aspects of a designed cognitive architecture for trustworthy HRI. This architecture, based on consolidated theoretical principles (theory of social adjustable autonomy, theory of mind, theory of trust) has the main goal to build cognitive robots that provide smart, trustworthy collaboration, every time a human requires their help. In particular, the experiment has been designed in order to demonstrate how the robot’s capability to learn its own level of self-trust on its predictive abilities in perceiving the user and building a model of her/him, allows it to establish a trustworthy collaboration and to maintain a high level of user’s satisfaction, with respect to the robot’s performance, also when these abilities progressively degrade.

On the Users’ Acceptance of IoT Systems: A Theoretical Approach

In the next future the IoT system will introduce extraordinary changes in our daily life. We will communicate with our domestic appliances to inform them about our preferences and goals and they will develop initiative and autonomy to be put at our service. But are we sure that we can afford all the automation they could offer? Are we able to manage it? Is it compatible with our cognitive attitudes and our actual and real goals? In this paper, we face the question of the IoT from the point of view of the user. We start analyzing which reasons undermine the acceptance of IoT systems and then we propose a possible solution. The first contribution of this work is the level characterization of the autonomy a user can grant to an IoT device. The second contribution is a theoretical model to deal with users and to stimulate users’ acceptance. By the means of simulation, we show how the model works and we prove that it leads the system to an optimal solution.

Control Architecture for Human–Robot Integration: Application to a Robotic Wheelchair

Completely autonomous performance of a mobile robot within noncontrolled and dynamic environments is not possible yet due to different reasons including environment uncertainty, sensor/software robustness, limited robotic abilities, etc. But in assistant applications in which a human is always present, she/he can make up for the lack of robot autonomy by helping it when needed. In this paper, the authors propose human-robot integration as a mechanism to augment/improve the robot autonomy in daily scenarios. Through the human-robot-integration concept, the authors take a further step in the typical human-robot relation, since they consider her/him as a constituent part of the human-robot system, which takes full advantage of the sum of their abilities. In order to materialize this human integration into the system, they present a control architecture, called architecture for human-robot integration, which enables her/him from a high decisional level, i.e., deliberating a plan, to a physical low level, i.e., opening a door. The presented control architecture has been implemented to test the human-robot integration on a real robotic application. In particular, several real experiences have been conducted on a robotic wheelchair aimed to provide mobility to elderly people.