Using genetic algorithms to optimize social robot behavior for improved pedestrian flow
Date
2005
Authors
Eldridge, Bryce D., author
Maciejewski, Anthony A., author
IEEE, publisher
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Abstract
This paper expands on previous research on the effect of introducing social robots into crowded situations in order to improve pedestrian flow. In this case, a genetic algorithm is applied to find the optimal parameters for the interaction model between the robots and the people. Preliminary results indicate that adding social robots to a crowded situation can result in significant improvement in pedestrian flow. Using the optimized values of the model parameters as a guide, these robots can be designed to be more effective at improving the pedestrian flow. While this work only applies to one situation, the technique presented can be applied to a wide variety of scenarios.
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Rights Access
Subject
crowd dynamics
genetic algorithms
social robots