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Decentralized Swarms Visibility Algorithms in 3D Urban Environments

Authors:
Oren Gal
Yerach Doytsher

Keywords: Swarm; Visibility; 3D; Urban environment; Decentralized 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 are comparing 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 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 algorithm 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 demonstrating performance analysis ,such as order, safety, connectivity and union.

Pages: 47 to 52

Copyright: Copyright (c) IARIA, 2022

Publication date: June 26, 2022

Published in: conference

ISSN: 2308-393X

ISBN: 978-1-61208-983-6

Location: Porto, Portugal

Dates: from June 26, 2022 to June 30, 2022