Shepherding Autonomous Goal-Focused Swarms in Unknown Environments Using Hilbert Space-Filling Paths

Nathan K. Long, Matthew Garratt, Karl Sammut, Daniel Sgarioto, Hussein A. Abbass

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


A novel technique has been developed for autonomous swarm-based unknown environment scouting. A control method known as swarm shepherding was employed, which replicates the behaviour seen when a sheepdog guides a herd of sheep to an objective location. The guidance of the swarm agents was implemented using low computation cost, force-based behaviours. The exploration task was augmented by introducing swarm member role assignments, including a role which imposes a localised covering area for agents which stray too far from the swarm global centre of mass. The agents then proceeded to follow a Hilbert space-filling curve (HSFC) path within their localised region. The simulation results demonstrated that the inclusion of the HSFC paths improved the efficiency of goal-based exploration of the environment, which became more prominent with an increase in the density of the number of goals in the environment.

Original languageEnglish
Title of host publicationShepherding UxVs for Human-Swarm Teaming
Subtitle of host publicationAn Artificial Intelligence Approach to Unmanned X Vehicles
EditorsHussein A. Abbass, Robert A. Hunjet
Place of PublicationSwitzerland
Number of pages20
ISBN (Electronic)9783030608989
ISBN (Print)9783030608972
Publication statusPublished - 2021

Publication series

NameUnmanned System Technologies
ISSN (Print)2523-3734
ISSN (Electronic)2523-3742


  • Herding
  • Hilbert space-filling curves
  • Robotic exploration
  • Shepherding
  • Swarm robotics


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