The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

Our understanding of social insect behavior has significantly influenced artificial intelligence (AI) and multirobot systems' research (e.g., ant algorithms and swarm robotics). In this work, however, we focus on the opposite question: "How can multirobot systems research contribute to the understanding of social animal behavior?" As we show, we are able to contribute at several levels. First, using algorithms that originated in the robotics community, we can track animals under observation to provide essential quantitative data for animal behavior research. Second, by developing and applying algorithms originating in speech recognition and computer vision, we can automatically label the behavior of animals under observation. In some cases the automatic labeling is more accurate and consistent than manual behavior identification. Our ultimate goal, however, is to automatically create, from observation, executable models of behavior. An executable model is a control program for an agent that can run in simulation (or on a robot). The representation for these executable models is drawn from research in multirobot systems programming. In this paper we present the algorithms we have developed for tracking, recognizing, and learning models of social animal behavior, details of their implementation, and quantitative experimental results using them to study social insects.

Notes

Number of pages: 19

Text Reference

Tucker Balch, Frank Dellaert, Adam Feldman, Andrew Guillory, Charles Isbell, Zia Khan, Stephen Pratt, Andrew Stein, and Hank Wilde, "How multirobot systems research will accelerate our understanding of social animal behavior," Proceedings of the IEEE, Vol. 94, No. 7, July, 2006, pp. 1445-1463.

BibTeX Reference

@article{Balch_2006_5544,
   author = "Tucker Balch and Frank Dellaert and Adam Feldman and Andrew Guillory and Charles Isbell and Zia Khan and Stephen Pratt and Andrew Stein and Hank Wilde",
   title = "How multirobot systems research will accelerate our understanding of social animal behavior",
   journal = "Proceedings of the IEEE",
   pages = "1445-1463",
   month = "July",
   year = "2006",
   volume = "94",
   number = "7",
}

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