Two dimensional swarming: Neighbour detection

Bachelor thesis (2022)

Authors

J.S. van Uffelen Electrical Engineering, Mathematics and Computer Science
L. de Kroon Electrical Engineering, Mathematics and Computer Science

Contributors

Ranga Rao Venkatesha Prasad Embedded Systems - EEMCS (supervisor 1)
A. Simha Embedded Systems - EEMCS (supervisor 1)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Jeroen van Uffelen, Lars de Kroon
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Published Date

21-06-2022

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Robot swarming has been done for quite some years now. However, creating a very large swarm can become very difficult, since the networking becomes complex. With small swarms, a robot can broadcast information, or a central node can coordinate the robots. However, when a swarm becomes very large, these techniques fall short. Broadcasting all information is too much to be evaluated by every single robot, and a central node can't control it as well.
In this research, we have looked at how nature works and tried to find a solution by mimicking its behaviour. In nature, animals stay in a swarm, based on their instinct combined with following their neighbours' behaviour.
This document is part of a bigger research which implements a bird-flocking algorithm with cars. For bird-flocking, the speed and heading of neighbours need to be known. Detection of neighbours with robots is technically challenging.
We have researched a way to detect neighbours based on a hardware filter based on RSSI, in combination with a software filter.