Navigation of Autonomous Swarm of Drones using Translational Coordinates

EasyChair Preprint 2971

Abstract

This work focuses on an autonomous swarm of drones, a multi-agent system, where the leader agent has the capability of intelligent decision making while the other agents in the swarm follow the leader blindly. The proposed algorithm helps with cost cutting especially in the multi-drone systems, i.e., swarms, by reducing the power consumption and processing requirements of each individual agent. It is shown that by applying a pre-specified formation design with feedback cross-referencing between the agents, the swarm as a whole can not only maintain the desired formation and navigate but also avoid collisions with obstacles and other drones. Furthermore, the power consumed by the nodes in the considered test scenario, is reduced by 50% by utilising the proposed methodology.

Keyphrases: Autonomous Swarm, Swarm Intelligence, Unmanned Aerial Vehicle, agent-based modeling, leader-follower, multi-agent systems

@booklet{EasyChair:2971,
  author    = {Jawad Yasin and Sherif Mohamed and Mohammad-Hashem Haghbayan and Jukka Heikkonen and Hannu Tenhunen and Juha Plosila},
  title     = {Navigation of Autonomous Swarm of Drones using Translational Coordinates},
  howpublished = {EasyChair Preprint 2971},
  year      = {EasyChair, 2020}}