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Navigation and Cooperative Control Using the AR.Drone Quadrotor

Authors:

Lucas Vago Santana,

Alexandre Santos Brandão,

Mário Sarcinelli-FilhoAuthors Info & Claims

Journal of Intelligent and Robotic Systems, Volume 84, Issue 1-4

Pages 327 - 350

https://doi.org/10.1007/s10846-016-0355-y

Published: 01 December 2016 Publication History

Abstract

This paper presents a computational system designed to perform autonomous indoor flights using low-cost equipment. Depending on the mission to be accomplished, one or two Parrot AR.Drone 2.0 quadrotors are supposed to fly in a three-dimensional workspace, guided by the navigation algorithms embedded in the proposed framework, which runs in a ground control computer. The tasks addressed involve positioning, trajectory tracking and leader-follower formation control. The key techniques required to solve such problems are reported in topics, including the mathematic modelling of the quadrotor, a model-based nonlinear flight controller and a state estimation strategy for sensory data fusion. The framework embeds the last two subsystems just mentioned, plus a communication link between the ground computer and the aircraft, to read the sensory data and to send the control signals necessary to guide the vehicle. Some experimental results are also presented and discussed, which allow concluding that the proposed methods are efficient in accomplishing the tasks addressed.

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Cited By

Wang XChen GGong HJiang JPaul ACheung SHo CDin S(2021)UAV swarm autonomous control based on Internet of Things and artificial intelligence algorithmsJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-18954140:4(7121-7133)Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.3233/JIFS-189541
Sultan MBiediger DLi BBecker A(2021)The Reachable Set of a Drone: Exploring the Position Isochrones for a Quadcopter2021 IEEE International Conference on Robotics and Automation (ICRA)10.1109/ICRA48506.2021.9561715(7679-7685)Online publication date: 30-May-2021
https://dl.acm.org/doi/10.1109/ICRA48506.2021.9561715
Santos MRosales CSarapura JSarcinelli-Filho MCarelli R(2019)An Adaptive Dynamic Controller for Quadrotor to Perform Trajectory Tracking TasksJournal of Intelligent and Robotic Systems10.1007/s10846-018-0799-393:1-2(5-16)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1007/s10846-018-0799-3
Show More Cited By

Navigation and Cooperative Control Using the AR.Drone Quadrotor
1. Computer systems organization
  1. Embedded and cyber-physical systems
2. Computing methodologies
  1. Artificial intelligence
    1. Control methods
    2. Planning and scheduling

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Information & Contributors

Information

Published In

cover image Journal of Intelligent and Robotic Systems

Journal of Intelligent and Robotic Systems Volume 84, Issue 1-4

December 2016

878 pages

ISSN:0921-0296

Issue’s Table of Contents

Copyright © Copyright © 2016 Springer Science+Business Media Dordrecht.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 December 2016

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Cited By

Wang XChen GGong HJiang JPaul ACheung SHo CDin S(2021)UAV swarm autonomous control based on Internet of Things and artificial intelligence algorithmsJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-18954140:4(7121-7133)Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.3233/JIFS-189541
Sultan MBiediger DLi BBecker A(2021)The Reachable Set of a Drone: Exploring the Position Isochrones for a Quadcopter2021 IEEE International Conference on Robotics and Automation (ICRA)10.1109/ICRA48506.2021.9561715(7679-7685)Online publication date: 30-May-2021
https://dl.acm.org/doi/10.1109/ICRA48506.2021.9561715
Santos MRosales CSarapura JSarcinelli-Filho MCarelli R(2019)An Adaptive Dynamic Controller for Quadrotor to Perform Trajectory Tracking TasksJournal of Intelligent and Robotic Systems10.1007/s10846-018-0799-393:1-2(5-16)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1007/s10846-018-0799-3
Rosales CSoria CRossomando F(2019)Identification and adaptive PID Control of a hexacopter UAV based on neural networksInternational Journal of Adaptive Control and Signal Processing10.1002/acs.295533:1(74-91)Online publication date: 7-Jan-2019
https://dl.acm.org/doi/10.1002/acs.2955

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