  An essential problem of swarm robotics is how members of the swarm knows the
positions of other robots. The main aim of this research is to develop a
cost-effective and simple vision-based system to detect the range, bearing, and
heading of the robots inside a swarm using a multi-purpose passive landmark. A
small Zumo robot equipped with Raspberry Pi, PiCamera is utilized for the
implementation of the algorithm, and different kinds of multipurpose passive
landmarks with nonsymmetrical patterns, which give reliable information about
the range, bearing and heading in a single unit, are designed. By comparing the
recorded features obtained from image analysis of the landmark through
systematical experimentation and the actual measurements, correlations are
obtained, and algorithms converting those features into range, bearing and
heading are designed. The reliability and accuracy of algorithms are tested and
errors are found within an acceptable range.
