Incorporating Mental Simulation for a More Effective Robotic Teammate

William Kennedy, Magdalena D. Bugajska, William Adams, Alan Schultz, Gregory Trafton

How can we facilitate human-robot teamwork? The teamwork literature has identified the need to know the capabilities of teammates. How can we integrate the knowledge of another agent’s capabilities for a justifiably intelligent teammate? This paper describes extensions to the cognitive architecture, ACT-R, and the use of artificial intelligence (AI) and cognitive science approaches to produce a more cognitively-plausible, autonomous robotic system that "mentally" simulates the decision-making of its teammate. The extensions to ACT-R added capabilities to interact with the real world through the robot’s sensors and effectors and simulate the decision-making of its teammate. The AI applications provided visual sensor capabilities by methods clearly different than those used by humans. The integration of these approaches into intelligent team-based behavior is demonstrated on a mobile robot. Our "TeamBot" matches the descriptive work and theories on human teamwork. We illustrate our approach in a spatial, team-oriented task of a guard force responding appropriately to an alarm condition that requires the human and robot team to "man" two guard stations as soon as possible after the alarm.

Subjects: 2. Architectures; 4. Cognitive Modeling

Submitted: Apr 15, 2008

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