Connectivity Preserving Decentralized UAV Swarm Navigation in Obstacle-laden Environments without Explicit Communication

Fuente: arXiv
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Autores principales: Palani, Thiviyathinesvaran, Fukushima, Hiroaki, Izuhara, Shunsuke
Formato: Preprint
Publicado: 2024
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author Palani, Thiviyathinesvaran
Fukushima, Hiroaki
Izuhara, Shunsuke
author_facet Palani, Thiviyathinesvaran
Fukushima, Hiroaki
Izuhara, Shunsuke
contents This paper presents a novel control method for a group of UAVs in obstacle-laden environments while preserving sensing network connectivity without data transmission between the UAVs. By leveraging constraints rooted in control barrier functions (CBFs), the proposed method aims to overcome the limitations, such as oscillatory behaviors and frequent constraint violations, of the existing method based on artificial potential fields (APFs). More specifically, the proposed method first determines desired control inputs by considering CBF-based constraints rather than repulsive APFs. The desired inputs are then minimally modified by solving a numerical optimization problem with soft constraints. In addition to the optimization-based method, we present an approximate method without numerical optimization. The effectiveness of the proposed methods is evaluated by extensive simulations to compare the performance of the CBF-based methods with an APF-based approach. Experimental results using real quadrotors are also presented.
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id arxiv_https___arxiv_org_abs_2411_19019
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Connectivity Preserving Decentralized UAV Swarm Navigation in Obstacle-laden Environments without Explicit Communication
Palani, Thiviyathinesvaran
Fukushima, Hiroaki
Izuhara, Shunsuke
Robotics
Systems and Control
This paper presents a novel control method for a group of UAVs in obstacle-laden environments while preserving sensing network connectivity without data transmission between the UAVs. By leveraging constraints rooted in control barrier functions (CBFs), the proposed method aims to overcome the limitations, such as oscillatory behaviors and frequent constraint violations, of the existing method based on artificial potential fields (APFs). More specifically, the proposed method first determines desired control inputs by considering CBF-based constraints rather than repulsive APFs. The desired inputs are then minimally modified by solving a numerical optimization problem with soft constraints. In addition to the optimization-based method, we present an approximate method without numerical optimization. The effectiveness of the proposed methods is evaluated by extensive simulations to compare the performance of the CBF-based methods with an APF-based approach. Experimental results using real quadrotors are also presented.
title Connectivity Preserving Decentralized UAV Swarm Navigation in Obstacle-laden Environments without Explicit Communication
topic Robotics
Systems and Control
url https://arxiv.org/abs/2411.19019