Particle swarm optimization algorithms for autonomous robots with deterministic leaders using space filling movements

In this work the swarm behavior principles of Craig W. Reynolds are combined with deterministic traits. This is done by
using leaders with motions based on space filling curves like Peano and Hilbert. Our goal is to evaluate how the swarm of
agents works with this approach, supposing the entire swarm will better explore the entire space. Therefore, we examine
different combinations of Peano and Hilbert with the already known swarm algorithms and test them in a practical challenge
for the harvesting of manganese nodules on the sea ground with the use of autonomous agents. We run experiments with
various settings, then evaluate and describe the results. In the last section some further development ideas and thoughts for
the expansion of this study are considered.