@inproceedings{3e3bf2bc6c9847c6a6c2687823d241e7,
title = "Planar formation control using tensegrity structures and experiments",
abstract = "This paper presents a framework on how to achieve prescribed planar formations using the concept of tensegrity structures. Given a group of robots with desired formation shape, we first design the underlying interaction topology based on the Polygon Theorem, yielding a super stable structure along with the robots' configuration. Then some basic control laws are introduced for mobile robots to model the interplay relationship between the neighbouring nodes in a self-equilibrated tensegrity structure. To fully validate the effectiveness of the tensegrity-motivated formation control strategy, we carry out not only numerical simulations but also experiments on two types of mobile robot platforms, wheeled mobile robots and unmanned aerial vehicles (UAVs).",
keywords = "Energy efficiency, Keyword: Predictive, Neural networks, Petrochemicals, Prediction algorithms, Production models, Training",
author = "Qingkai Yang and Yunlong Pan and Bo Zhou and Hao Fang",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE; 34rd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2019 ; Conference date: 06-06-2019 Through 08-06-2019",
year = "2019",
month = jun,
doi = "10.1109/YAC.2019.8787707",
language = "English",
series = "Proceedings - 2019 34rd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "307--311",
booktitle = "Proceedings - 2019 34rd Youth Academic Annual Conference of Chinese Association of Automation, YAC 2019",
address = "United States",
}
