No abstract

To study how robots can work better with humans as a team, we have designed an agent-based online testbed that supports virtual simulation of domain-independent human-robot interaction. The simulation is implemented as an online game where humans and virtual robots work together in simulated scenarios. This testbed allows researchers to carry out human-robot interaction studies and gain better understanding of, for example, how a robot's communication can improve human-robot team performance by fostering better trust relationships among humans and their robot teammates. In this paper, we discuss the requirements, challenges and the design of such human-robot simulation. We illustrate its operation with an example human-robot joint reconnaissance task.

Abstract. State-of-the-art computer graphics can give autonomous agents a compelling appearance as animated virtual characters. Typically the agents are directly responsible for controlling their graphical representation, but this places too much burden on the agents that already deal with difficult high-level tasks such as dialog planning. This paper presents work, done in the context of an interactive language and culture training system, on a new kind of engine that fits between the high level cognitive agent models and the animated graphics that represent them. This is a social engine that generates socially appropriate nonverbal behavior based on rules reflecting social norms. Similar to modular physics engines, the social engine introduces a re-usable component that can heighten believability of animated agents in games and simulations with relatively little effort.

No abstract