Simulating swarm robots for collision avoidance problem based on a dynamic Bayesian network

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper presents a simulator for the behaviors of swarm robots based on a Dynamic Bayesian Network (DBN). Our task is to design each robot's controller which enables the robot to patrol as many regions as possible without collisions. As the first step, we use two swarm robots, each of which has two motors each of which is connected to a wheel and three distance-measurement sensors. To design the controllers of these robots, we must determine several parameters such as the motor speed and thresholds of the three sensors. The simulator is used to reduce the number of real experiments in deciding values of such parameters. We fist performed measurement experiments for our real robots in order to get probabilistic data of the DBN. The simulator based on the DBN revealed appropriate values of a threshold parameter and interesting phase transitions of their behaviors in terms of the values.

Original languageEnglish
Title of host publicationAdvances in Artificial Life
Subtitle of host publicationDarwin Meets von Neumann - 10th European Conference, ECAL 2009, Revised Selected Papers
Number of pages8
EditionPART 2
Publication statusPublished - Jul 11 2011
Event10th European Conference of Artificial Life, ECAL 2009 - Budapest, Hungary
Duration: Sept 13 2009Sept 16 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5778 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other10th European Conference of Artificial Life, ECAL 2009

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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