Formation control of unmanned micro aerial vehicles for straitened environments

Saska, Martin; Heřt, Daniel; Báča, Tomáš; Krátký, Vít; Nascimento, Tiago P.

doi:10.1007/s10514-020-09913-0

Cited by 22 publications

(13 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The development of flocking algorithms in swarm robotics commonly uses ground robots in indoor environments mainly due to the simpleness of the environment setup. Basic research in the area of UAV flocking and formation flying was recently studied in [13]. Our results demonstrated that the proposed method works on UAVs.…”

Section: Discussionmentioning

confidence: 62%

Self-Organized UAV Flocking Based Only on Relative Range and Bearing

Amorim

Nascimento

2021

Revista CI

Self Cite

View full text Add to dashboard Cite

In this work, we address the problem of convergence and cohesiveness of an unmanned aerial vehicle (UAV) flocking. Thus, we propose a proximal control-based method for UAV self-organized flocking. Our method efficiently achieves flocking in the absence of alignment control and moves into an arbitrary direction without any direction control or informed robots. Robots use a Lennard-Jones potential function to maintain the cohesiveness of the flocking while avoiding collision within the teammates. We evaluate our approach using the order metric, the steady-state value, and the settling time that can be used as a cohesiveness indicator.

show abstract

Section: Discussionmentioning

confidence: 62%

Self-Organized UAV Flocking Based Only on Relative Range and Bearing

Amorim

Nascimento

2021

Revista CI

Self Cite

View full text Add to dashboard Cite

show abstract

“…In contrast, admittance tracking is used to mitigate excessive control errors due to the UAV being trapped on the ground by an unwanted mechanical attachment during take-off. In addition, research on UAV swarming [36,37] often requires more direct access to the desired states of the UAV. For those situations, we provide the Speed tracker, which allows direct control of the desired speed and/or acceleration of the UAV, while maintaining the desired height and heading.…”

Section: Reference Trackersmentioning

confidence: 99%

“…Basic research in the area of UAV swarming and formation flying was studied in [36,37,62]. UAV swarm control is a relatively new field of research, and its applications are yet to be explored.…”

Section: Uav Swarms and Formationsmentioning

confidence: 99%

The MRS UAV System: Pushing the Frontiers of Reproducible Research, Real-world Deployment, and Education with Autonomous Unmanned Aerial Vehicles

Baca,

Petrlik,

Vrba

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

We present a multirotor Unmanned Aerial Vehicle (UAV) control and estimation system for supporting replicable research through realistic simulations and real-world experiments. We propose a unique multi-frame localization paradigm for estimating the states of a UAV in various frames of reference using multiple sensors simultaneously. The system enables complex missions in GNSS and GNSS-denied environments, including outdoor-indoor transitions and the execution of redundant estimators for backing up unreliable localization sources. Two feedback control designs are presented: one for precise and aggressive maneuvers, and the other for stable and smooth flight with a noisy state estimate. The proposed control and estimation pipeline are constructed without using the Euler/Tait-Bryan angle representation of orientation in 3D. Instead, we rely on rotation matrices and a novel heading-based convention to represent the one free rotational degree-of-freedom in 3D of a standard multirotor helicopter. We provide an actively maintained and well-documented open-source implementation (http://github.com/ctu-mrs/mrs_uav_system), including realistic simulation of UAVs, sensors, and localization systems. The proposed system is the product of years of applied research on multi-robot systems, aerial swarms, aerial manipulation, motion planning, and remote sensing. All our results have been supported by real-world system deployment that subsequently shaped the system into the form presented here. In addition, the system was utilized during the participation of our team from the Czech Technical University in Prague in the prestigious MBZIRC 2017 and 2020 robotics competitions, and also in the DARPA Subterranean challenge. Each time, our team was able to secure top places among the best competitors from all over the world. On each occasion, the competitions and challenges has motivated the team to improve the system and to gain a great amount of high-quality experience within tight deadlines.

show abstract

“…From last few years of research, it is observed that the cyber physical system has become an emergence field because of its increasing development in the field of complex coordination system (Chen et al, 2020; Gelbal et al, 2020; Villarreal-Cervantes et al, 2020). Examples of these coordination systems are autonomous systems (Chehardoli, 2020; Shi and Zhang, 2020; Zhang et al, 2018), robotic systems (Yao et al, 2020), unmanned aerial vehicles, formation control (Saska et al, 2020), and distributed electrical systems (Huang and Wang, 2020; Gavriluta et al, 2020). As a classical cyber physical system, these all consist of number of agents called networked multi-agent systems (NMASs) and these agents share their information with each other through a communication medium (Ge et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Frequency domain consensus control analysis of the networked multi-agent system with controller area network bus–induced delay

Nasir

Hayat

Jamal

et al. 2021

Journal of Vibration and Control

View full text Add to dashboard Cite

This article describes the consensus control issue of networked multi-agent system with controller area network bus–induced delay in the frequency domain. Initially, causes of the controller area network bus–induced delay in distributed networked control systems and features of controller area network buses are analyzed. Then, networked multi-agent systems composed of distributed networked control systems are modeled in the frequency domain. An analytical controller based on the parameterization technique is proposed to improve the H2 performance criterion of distributed networked control systems. The performance tracking and robustness of the controller is analyzed by its sensitivity functions. After the performance and robustness analysis, the delay margin criteria and consensus conditions of networked multi-agent systems are derived in the existence of controller area network bus–induced delay. We verify the efficiency of the proposed method by simulating examples.

show abstract

Formation control of unmanned micro aerial vehicles for straitened environments

Cited by 22 publications

References 47 publications

Self-Organized UAV Flocking Based Only on Relative Range and Bearing

Self-Organized UAV Flocking Based Only on Relative Range and Bearing

The MRS UAV System: Pushing the Frontiers of Reproducible Research, Real-world Deployment, and Education with Autonomous Unmanned Aerial Vehicles

Frequency domain consensus control analysis of the networked multi-agent system with controller area network bus–induced delay

Contact Info

Product

Resources

About