@inbook {2013n-SpeNotBueFra,
	title = {Aggressive Maneuver Regulation of a Quadrotor UAV},
	booktitle = {Robotics Research, The 16th International Symposium ISRR},
	volume = {114},
	number = {Springer Tracts in Advanced Robotics},
	year = {2016},
	month = {04/2016},
	pages = {95-112},
	publisher = {Springer},
	organization = {Springer},
	abstract = {In this paper we design a nonlinear controller for aggressive maneuvering of a quadrotor. We take a maneuver regulation perspective. Differently from the classical trajectory tracking approach, maneuver regulation does not require following a timed reference state, but a geometric {\textquotedblleft}path{\textquotedblright} with a velocity (and possibly orientation) profile assigned on it. The proposed controller re- lies on three main ideas. Given a desired maneuver, i.e., a set of state trajectories equivalent under time translations, the system dynamics is decomposed into dynamics longitudinal and transverse to the maneuver. A space-dependent version of the transverse dynamics is derived, by using the longitudinal state, i.e., the arc-length of the path, as an independent variable. Then the controller is obtained as a function of the arc-length consisting of two terms: a feedforward term, being the nominal input to apply when on the path at the current arc-length, and a feedback term exponentially stabilizing the state-dependent transverse dynamics. Numerical computations are presented to prove the effectiveness of the proposed strategy. The controller performances are tested in presence of uncertainty of the model parameters and input noise and saturations. The controller is also tested in a realistic simulation environment validated against an experimental test-bed.},
	keywords = {Aerial Robotics},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2013n-SpeNotBueFra-preprint.pdf , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2013n-SpeNotBueFra-1_no_sat.mp4 , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2013n-SpeNotBueFra-1_no_sat_zoom.mp4 , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2013n-SpeNotBueFra-2_sat_8_5.mp4 , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2013n-SpeNotBueFra-2_sat_8_5_zoom.mp4 , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2013n-SpeNotBueFra-2_sat_7.mp4 , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2013n-SpeNotBueFra-2_sat_7_zoom.mp4},
	author = {Sara Spedicato and Giuseppe Notarstefano and Heinrich H. B{\"u}lthoff and Antonio Franchi}
}
@conference {2016a-SpeFraNot,
	title = {From Tracking to Robust Maneuver Regulation: an Easy-to-Design Approach for VTOL Aerial Robots},
	booktitle = {2016 IEEE Int. Conf. on Robotics and Automation},
	year = {2016},
	month = {05/2016},
	pages = {2965-2970},
	address = {Stockholm, Sweden},
	abstract = {In this paper we present a maneuver regulation scheme for Vertical Take-Off and Landing (VTOL) micro aerial vehicles (MAV). Differently from standard trajectory tracking, maneuver regulation has an intrinsic robustness due to the fact that the vehicle is not required to chase a virtual target, but just to stay on a (properly designed) desired path with a given velocity profile. In this paper we show how a robust maneuver regulation controller can be easily designed by converting an existing tracking scheme. The resulting maneuvering controller has three main appealing features, namely it: (i) inherits the robustness properties of the tracking controller, (ii) gains the appealing features of maneuver regulation, and (iii) does not need any additional tuning with respect to the tracking controller. We prove the correctness of the proposed scheme and show its effectiveness in experiments on a nano-quadrotor. In particular, we show on a nontrivial maneuver how external disturbances acting on the quadrotor cause instabilities in the standard tracking, while marginally affect the maneuver regulation scheme.},
	keywords = {Aerial Robotics},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2016a-SpeFraNot-preprint.pdf , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2016a-SpeFraNot.mp4},
	author = {Sara Spedicato and Antonio Franchi and Giuseppe Notarstefano}
}
