Simultaneous estimation of aerodynamic and contact forces in flying robots: Applications to metric wind estimation and collision detection

In this paper, we extend our previous external wrench estimation scheme for flying robots with an aerodynamic model such that we are able to simultaneously estimate aerodynamic and contact forces online. This information can be used to identify the metric wind velocity vector via model inversion. Noticeably, we are still able to accurately sense collision forces at the same time. Discrimination between the two is achieved by identifying the natural contact frequency characteristics for both “interaction cases”. This information is then used to design suitable filters that are able to separate the aerodynamic from the collision forces for subsequent use. Now, the flying system is able to correctly respond to typical contact forces and does not accidentally “hallucinate” contacts due to a misinterpretation of wind disturbances. Overall, this paper generalizes our previous results towards significantly more complex environments.

[1]  Teodor Tomic Evaluation of acceleration-based disturbance observation for multicopter control , 2014, 2014 European Control Conference (ECC).

[2]  Roland Siegwart,et al.  Towards Estimation and Correction of Wind Effects on a Quadrotor UAV , 2014 .

[3]  Robert E. Mahony,et al.  Aerodynamic power control for multirotor aerial vehicles , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[4]  Robert Mahony,et al.  Nonlinear Dynamic Modeling for High Performance Control of a Quadrotor , 2012, ICRA 2012.

[5]  Gamini Dissanayake,et al.  Model-aided state estimation for quadrotor micro air vehicles amidst wind disturbances , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[6]  Philippe Martin,et al.  The true role of accelerometer feedback in quadrotor control , 2010, 2010 IEEE International Conference on Robotics and Automation.

[7]  Vincenzo Lippiello,et al.  Impedance control of VToL UAVs with a momentum-based external generalized forces estimator , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[8]  Michael S. Selig,et al.  Propeller Performance Data at Low Reynolds Numbers , 2011 .

[9]  Tarek Hamel,et al.  Nonlinear control of VTOL UAVs incorporating flapping dynamics , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  Steven L. Waslander,et al.  Wind Disturbance Estimation and Rejection for Quadrotor Position Control , 2009 .

[11]  Duane T. McRuer,et al.  Aircraft Dynamics and Automatic Control , 1973 .

[12]  Antonio Franchi,et al.  A nonlinear force observer for quadrotors and application to physical interactive tasks , 2014, 2014 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

[13]  Rogelio Lozano,et al.  Trajectory Control of a Quadrotor Subject to 2D Wind Disturbances , 2013, J. Intell. Robotic Syst..

[14]  Tarek Hamel,et al.  Hardware and Software Architecture for Nonlinear Control of Multirotor Helicopters , 2013, IEEE/ASME Transactions on Mechatronics.

[15]  Sami Haddadin,et al.  A unified framework for external wrench estimation, interaction control and collision reflexes for flying robots , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[16]  Stefano Stramigioli,et al.  Contact impedance estimation for robotic systems , 2005, IEEE Trans. Robotics.

[17]  J. Gordon Leishman,et al.  Principles of Helicopter Aerodynamics , 2000 .

[18]  Steven Lake Waslander,et al.  Aerodynamics and control of autonomous quadrotor helicopters in aggressive maneuvering , 2009, 2009 IEEE International Conference on Robotics and Automation.

[19]  Stefano Stramigioli,et al.  Contact impedance estimation for robotic systems , 2004, IEEE Transactions on Robotics.