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Analysis of Bee Activity for Biologically Inspired Robot Design

Biology Friday, December 12, 2003 . This is a SciScoop post by gpmap

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From Georgia Tech Research News: A new computer vision system for automated analysis of animal movement — honey bee activities, in particular — is expected to accelerate animal behavior research, which also has implications for biologically inspired design of robots and computers.
The animal movement analysis system is part of the BioTracking Project, an effort conducted by Georgia Institute of Technology robotics researchers led by Tucker Balch, an assistant professor of computing.
“We believe the language of behavior is common between robots and animals,” Balch said. “That means, potentially, that we could videotape ants for a long period of time, learn their ‘program’ and run it on a robot.”
Social insects, such as ants and bees, represent the existence of successful large-scale, robust behavior forged from the interaction of many, simple individuals, Balch explained. Such behavior can offer ideas on how to organize a cooperating colony of robots capable of complex operations.
To expedite the understanding of such behavior, Balch’s team developed a computer vision system that automates analysis of animal movement — once an arduous and time-consuming task. Researchers are using the system to analyze data on the sequential movements that encode information — for example in bees, the location of distant food sources, Balch said. He will present the research at the Second International Workshop on the Mathematics and Algorithms of Social Insects on Dec. 16-17 at Georgia Tech.

1 Response to Analysis of Bee Activity for Biologically Inspired Robot Design

ChiefTechnovelgist

December 15th, 2003 at 5:20 pm

I found an interesting related link to this story on the subject of swarm engineering. Lots of simple robots following simple rules can accomplish complex tasks more easily than a single large robot.

Thus, swarm engineering consists of two related steps. The first step is to propose an expression of the problem which leads to a set of conditions on the individual agents which, when satisfied, will complete the task. The second step is to produce a behavior or set of behaviors for one or many robots which accomplishes these requirements.

See Swarm Engineering

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