Output feedback control of Micro Aerial Vehicle in indoor environment

A novel approach for control of a Micro Air Vehicle in indoor environment (specifically within corridors) using only vision and angular velocity sensors as measuring devices is presented. The suggested controller does not include explicit attitude feedback, thus eliminating the need for accelerometers which are susceptible to vibrations, and complex attitude estimation algorithms. Furthermore, linear velocity measurement which can be difficult to achieve in indoor environment is not required to damp the system. A model for the hovercraft and visual measurements is presented, and stability analysis of the suggested controller is performed and supported by a complete six degrees of freedom simulation.

[1]  Angela P. Schoellig,et al.  Improving tracking performance by learning from past data , 2012 .

[2]  Roland Siegwart,et al.  Vision based MAV navigation in unknown and unstructured environments , 2010, 2010 IEEE International Conference on Robotics and Automation.

[3]  Markus Hehn,et al.  A flying inverted pendulum , 2011, 2011 IEEE International Conference on Robotics and Automation.

[4]  Vijay Kumar,et al.  Trajectory generation and control for precise aggressive maneuvers with quadrotors , 2012, Int. J. Robotics Res..

[5]  Timothy W. McLain,et al.  Quadrotors and Accelerometers: State Estimation with an Improved Dynamic Model , 2014, IEEE Control Systems.

[6]  P. Olver Nonlinear Systems , 2013 .

[7]  Mario J. Valenti,et al.  Estimation and Control of a Quadrotor Vehicle Using Monocular Vision and Moire Patterns , 2006 .

[8]  Angela Scḧollig,et al.  A Platform for Dance Performances with Multiple Quadrocopters , 2010 .

[9]  Rogelio Lozano,et al.  Stabilization and Trajectory Tracking of a Quad-Rotor Using Vision , 2011, J. Intell. Robotic Syst..

[10]  Ashutosh Saxena,et al.  Autonomous MAV flight in indoor environments using single image perspective cues , 2011, 2011 IEEE International Conference on Robotics and Automation.

[11]  Daniel Cremers,et al.  Scale-aware navigation of a low-cost quadrocopter with a monocular camera , 2014, Robotics Auton. Syst..

[12]  Robert Mahony,et al.  Modelling and control of a quad-rotor robot , 2006 .

[13]  周兆英,et al.  Attitude Determination for MAVs Using a Kalman Filter , 2008 .

[14]  Nabil Aouf,et al.  Visual servoing of a Quadrotor UAV for autonomous power lines inspection , 2014, 22nd Mediterranean Conference on Control and Automation.

[15]  Roland Siegwart,et al.  Backstepping and Sliding-mode Techniques Applied to an Indoor Micro Quadrotor , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[16]  Tarek Hamel,et al.  A coupled estimation and control analysis for attitude stabilisation of mini aerial vehicles , 2006 .

[17]  Mark Euston,et al.  A complementary filter for attitude estimation of a fixed-wing UAV , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[18]  Roland Siegwart,et al.  Real-time onboard visual-inertial state estimation and self-calibration of MAVs in unknown environments , 2012, 2012 IEEE International Conference on Robotics and Automation.