Using genetic algorithms to optimize social robot behavior for improved pedestrian flow Eldridge, Bryce D. ; Maciejewski, Anthony A. 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. Colorado State University. Libraries 2005 text ; image application/pdf ECEaam00113.pdf FACFECEN100113ARTI eng c2005 IEEE
Using genetic algorithms to optimize social robot behavior for improved pedestrian flow
Eldridge, Bryce D. ; Maciejewski, Anthony A.
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.
Colorado State University. Libraries
2005
text ; image
application/pdf
ECEaam00113.pdf
FACFECEN100113ARTI
eng
c2005 IEEE