Landing of an Ardrone 2.0 quadcopter on a mobile base using fuzzy logic

In this paper, a fuzzy control system is presented for an unmanned aerial vehicle (UAV) which provides aerial support for an unmanned ground vehicle (UGV). The UGV acts as a mobile launching pad for the UAV. The UAV provides additional environmental image feedback to the UGV. Our UAV of choice is a Parrot ArDrone 2.0 quadcopter, a small four rotored aerial vehicle, competent for its agile flight and video feedback capabilities. This paper presents design and simulation of fuzzy logic controllers for performing landing and altitude control. Image processing and Mamdani-type inference are used for converting sensor input into control signals used to control the UAV.

[1]  Steven Lake Waslander,et al.  Coordinated landing of a quadrotor on a skid-steered ground vehicle in the presence of time delays , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Syed Ali Raza,et al.  Intelligent Flight Control of an Autonomous Quadrotor , 2010 .

[3]  Claire J. Tomlin,et al.  Learning-based model predictive control on a quadrotor: Onboard implementation and experimental results , 2012, 2012 IEEE International Conference on Robotics and Automation.

[4]  A. M. Shahri,et al.  Decentralized adaptive stabilization control for a quadrotor UAV , 2013, 2013 First RSI/ISM International Conference on Robotics and Mechatronics (ICRoM).

[5]  Jesús Alcalá-Fdez,et al.  jFuzzyLogic: a robust and flexible Fuzzy-Logic inference system language implementation , 2012, 2012 IEEE International Conference on Fuzzy Systems.

[6]  Jonathan P. How,et al.  Automated Battery Swap and Recharge to Enable Persistent UAV Missions , 2011 .

[7]  G. Barbastathis,et al.  Autonomous landing of an Unmanned Aerial Vehicle on an autonomous marine vehicle , 2012, 2012 Oceans.

[8]  Andreas Zell,et al.  Automatic Take Off, Tracking and Landing of a Miniature UAV on a Moving Carrier Vehicle , 2011, J. Intell. Robotic Syst..

[9]  Vijay Kumar,et al.  Towards a swarm of agile micro quadrotors , 2012, Robotics: Science and Systems.

[10]  Martin Buss,et al.  Visual tracking and control of a quadcopter using a stereo camera system and inertial sensors , 2009, 2009 International Conference on Mechatronics and Automation.

[11]  Daniel Cremers,et al.  Accurate Figure Flying with a Quadrocopter Using Onboard Visual and Inertial Sensing , 2012 .

[12]  Kenzo Nonami,et al.  A visual navigation system for autonomous flight of micro air vehicles , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[13]  Holger Voos,et al.  Nonlinear tracking and landing controller for quadrotor aerial robots , 2010, 2010 IEEE International Conference on Control Applications.

[14]  Oskar von Stryk,et al.  Comprehensive Simulation of Quadrotor UAVs Using ROS and Gazebo , 2012, SIMPAR.

[15]  Alireza Mohammad Shahri,et al.  Modelling and decentralized adaptive tracking control of a quadrotor UAV , 2013, 2013 First RSI/ISM International Conference on Robotics and Mechatronics (ICRoM).

[16]  Kazuya Yoshida,et al.  Collaborative mapping of an earthquake‐damaged building via ground and aerial robots , 2012, J. Field Robotics.