Design of a vision based range bearing and heading system for robot swarms

TL;DR

This paper presents a simple, cost-effective vision-based system using passive landmarks for robots in a swarm to determine their relative positions and orientations, enhancing coordination.

Contribution

It introduces a novel passive landmark design and algorithms for accurate range, bearing, and heading estimation using a Raspberry Pi and PiCamera in swarm robots.

Findings

Algorithms achieve reliable position and orientation estimation within acceptable error margins.

Passive landmarks with nonsymmetrical patterns effectively encode spatial information.

System tested on Zumo robots with promising accuracy.

Abstract

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.