Shout and Act

  • Authors:
  • Josep Lluis de la Rosa;Albert Trias;Antoni Martorano;Eloi Colomeda;David Huerva;Esteve del Acebo

  • Affiliations:
  • EASY Innovation Center --TECNIO @ University of Girona and Rensselaer Polytechnic Institute (RPI);EASY Innovation Center --TECNIO @ University of Girona;EASY Innovation Center --TECNIO @ University of Girona;EASY Innovation Center --TECNIO @ University of Girona;EASY Innovation Center --TECNIO @ University of Girona;EASY Innovation Center --TECNIO @ University of Girona

  • Venue:
  • Proceedings of the 2009 conference on Artificial Intelligence Research and Development: Proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Shout and Act (S&A) is an evolution of Bar Systems, a family of algorithms for different classes of complex optimization problems in static and dynamic environments by reactive multi agent systems. We adapt these systems to RoboRescue, where robots explore land looking for victims. When they find someone they “shout” so that robot mates can hear it. The louder the shout, the most important or urgent the finding. Louder shouts can also refer to closeness. Several experiments show that this system works very scalably, and how heterogeneous teams of robots outperform homogeneous ones over a range of task complexity. Finally, our results impact the design of RoboRescue teams: a properly designed combination of robots is cheaper and more scalable when confronted with uncertain maps of victims.