@inproceedings{8582051ed74b4f5591d416b446822912,
title = "Collective Gradient Following with Sensory Heterogeneous UAV Swarm",
abstract = "In this paper, we present a new method for a swarm to collectively sense and follow a gradient in the environment. The agents in the swarm only rely on relative distance and bearing measurements of neighbors. Additionally, only a minority of agents in the swarm perceive the scalar value of the gradient at their location. We test the method with incrementally changing ratio of agents with sensors on various swarm sizes. In addition to repeated simulation experiments, we also test the performance with a real nano-drone swarm. Results show us that, using the new method, the swarm was successful at following the gradient in the environment even with a low portion of the swarm with sensors on various swarm sizes. A real nano-drone swarm also demonstrates a good performance in our test even with members having disabled sensors.",
keywords = "collective sensing, nano-drone swarm, sensor heterogeneity",
author = "Karag{\"u}zel, {Tugay Alperen} and Nicolas Cambier and Eiben, {A. E.} and Eliseo Ferrante",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; 16th International Symposium on Distributed Autonomous Robotic Systems, DARS 2022 ; Conference date: 28-11-2022 Through 30-11-2022",
year = "2024",
doi = "10.1007/978-3-031-51497-5_14",
language = "English (US)",
isbn = "9783031514968",
series = "Springer Proceedings in Advanced Robotics",
publisher = "Springer Nature",
pages = "187--201",
editor = "Julien Bourgeois and Beno{\^i}t Piranda and Sabine Hauert and Heiko Hamann and Fumitoshi Matsuno and Abdallah Makhoul and Jamie Paik and Justin Werfel and Alyssa Pierson and Lam, {Tin Lun} and Negar Mehr",
booktitle = "Distributed Autonomous Robotic Systems - 16th International Symposium",
address = "United States",
}