Home // International Journal On Advances in Intelligent Systems, volume 15, numbers 3 and 4, 2022 // View article

Visibility-based Decentralized Swarm Decision Making Algorithms in 3D Urban Environments

Authors:
Oren Gal
Yerach Doytsher

Keywords: Swarm; Visibility; 3D; Urban environment; Decentlized algorithms.

Abstract:
In this paper, we present a unique and efficient visible trajectory planning for aerial swarm using decentralized algorithms in a 3D urban environment. By using SwarmLab environment, we compare two decentralized algorithms from the state of the art for the navigation of aerial swarms, Olfati-Saber’s and Vasarhelyi’s. The first step in our concept is to extract basic geometric shapes. We focus on three basic geometric shapes from point clouds in urban scenes that can be appear: planes, cylinders and spheres, extracting these geometric shapes using efficient Random Sample Consensus (RANSAC) algorithms with a high success rate of detection. The second step is a decentralized swarm algorithms for motion planning, demonstrated on drones in urban environment. Our planner includes dynamic and kinematic platform’s limitation, generating visible trajectories based on our first step mentioned earlier. We demonstrate our visibility and trajectory planning method in simulations, showing trajectory planning in 3D urban environments for drone’s swarm with decentralized algorithms with performance analysis such as order, safety, connectivity and union.

Pages: 201 to 209

Copyright: Copyright (c) to authors, 2022. Used with permission.

Publication date: December 31, 2022

Published in: journal

ISSN: 1942-2679