Evolution of fuzzy behaviors for multi-robotic system

  • Authors:

  • Prahlad Vadakkepat;Xiao Peng;Boon Kiat Quek;Tong Heng Lee

  • Affiliations:

  • Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117576 Singapore, Singapore;Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117576 Singapore, Singapore;Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117576 Singapore, Singapore;Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117576 Singapore, Singapore

  • Venue:
  • Robotics and Autonomous Systems
  • Year:
  • 2007

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Abstract

In a multi-robotic system, robots interact with each other in a dynamically changing environment. The robots need to be intelligent both at the individual and group levels. In this paper, the evolution of a fuzzy behavior-based architecture is discussed. The behavior-based architecture decomposes the complicated interactions of multiple robots into modular behaviors at different complexity levels. The fuzzy logic approach brings in human-like reasoning to the behavior construction, selection and coordination. Various behaviors in the fuzzy behavior-based architecture are evolved by genetic algorithm (GA). At the lowest level of the architecture hierarchy, the evolved fuzzy controllers enhanced the smoothness and accuracy of the primitive robot actions. At a higher level, the individual robot behaviors have become more skillful after the evolution. At the topmost level, the evolved group behaviors have resulted in aggressive competition strategy. The simulation and real-world experimentation on a robot-soccer system justify the effectiveness of the approach.