We present a new technique for human-robot interaction called robot expressionism through cartooning. We suggest that robots utilise cartoon-art techniques such as simplified and exaggerated facial expressions, stylised text, and icons for intuitive social interaction with humans. We discuss practical mixed reality solutions that allow robots to augment themselves or their surroundings with cartoon art content. Our effort is part of what we call robot expressionism, a conceptual approach to the design and analysis of robotic interfaces that focuses on providing intuitive insight into robotic states as well as the artistic quality of interaction. Our paper discusses a variety of ways that allow robots to use cartoon art and details a test bed design, implementation, and exploratory evaluation. We describe our test bed, Jeeves, which uses a Roomba, an iRobot vacuum cleaner robot, and a mixed-reality system as a platform for rapid prototyping of cartoon-art interfaces. Finally, we present a set of interaction content scenarios which use the Jeeves prototype: trash Roomba, the recycle police, and clean tracks, as well as initial exploratory evaluation of our approach.

Interaction with a remote team of robots in real time is a difficult human-robot interaction (HRI) problem exacerbated by the complications of unpredictable realworld environments, with solutions often resorting to a larger-than-desirable ratio of operators to robots. We present two innovative interfaces that allow a single operator to interact with a group of remote robots. Using a tabletop computer the user can configure and manipulate groups of robots directly by either using their fingers (touch) or by manipulating a set of physical toys (tangible user interfaces). We recruited participants to partake in a user study that required them to interact with a small group of remote robots in simple tasks, and present our findings as a set of design considerations.

A reusable agent-based generic model is presented for a specific class of Ambient Intelligence applications: those cases addressing human wellbeing and functioning from a human-like understanding. The model incorporates ontologies, knowledge and dynamic models from human-directed sciences such as psychology, social science, neuroscience and biomedical sciences. The model has been formally specified, and it is shown how for specific applications it can be instantiated by application-specific elements, thus providing an executable specification that can be used for prototyping. Moreover, it is shown how dynamic properties can be formally specified and verified against generated traces.