@article {2018v-AreMerFra,
	title = {A Novel Experimental Model and a Drag-optimal Allocation Method for Variable-Pitch Propellers in Multirotors},
	journal = {IEEE Access},
	volume = {6},
	year = {2018},
	month = {11/2018},
	pages = {68155-68168},
	abstract = {This paper proposes a new mathematical model to map the rotational speed and angle of attack (pitch) of small- size propellers typically used in multirotors and the aerodynamic thrust force and drag moment produced by the propeller itself. The new model is inspired by standard models using the blade- element and momentum theories, which have been suitably modified in order to allow for explicit fast computation of the direct and inverse map (useful for high-frequency control) and obtain a better adherence to experimental data. The new model allows and captures all the main nonlinear characteristics of the thrust/drag generation. An extensive experimental comparison shows that the prediction capability of the proposed model outperforms the most commonly used models at date. In the second part of the paper, two optimization methods are proposed in order to exploit the redundancy of the inputs of variable-pitch propellers to decrease the power consumption due to the drag dissipation. The first method deals with optimal allocation for thrust generation on a single propeller, while the second method is aimed at solving the optimal allocation of the rotational speed and pitch of all the propellers in a multi-rotor with any number of propellers. Simulations results show the viability and effectiveness of the proposed methods.},
	doi = {10.1109/ACCESS.2018.2879636},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2018v-AreMerFra-preprint.pdf},
	author = {Victor Arellano-Quintana and Emmanuel Merchan-Cruz and Antonio Franchi}
}
@conference {2018g-BicStaSabAreMisFra,
	title = {Towards a Flying Assistant Paradigm: the OTHex},
	booktitle = {2018 IEEE Int. Conf. on Robotics and Automation},
	year = {2018},
	month = {05/2018},
	pages = {6997-7002},
	address = {Brisbane, Australia},
	abstract = {This paper presents the OTHex platform for aerial manipulation developed at LAAS{\textendash}CNRS. The OTHex is probably the first multi-directional thrust platform designed to act as Flying Assistant which can aid human operators and/or Ground Manipulators to move long bars for assembly and maintenance tasks. The work emphasis is on task-driven custom design and experimental validations. The proposed control framework is built around a low-level geometric controller, and includes an external wrench estimator, an admittance filter, and a trajectory generator. This tool gives the system the necessary compliance to resist external force disturbances arising from contact with the surrounding environment or to parameter uncertainties in the load. A set of experiments validates the real-world applicability and robustness of the overall system.},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2018g-BicStaSabAreMisFra-preprint.pdf , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2018g-BicStaSabAreMisFra.mp4},
	author = {Nicolas Staub and Davide Bicego and Quentin Sabl{\'e} and Victor Arellano-Quintana and Subodh Mishra and Antonio Franchi}
}
@conference {2017h-SanAreTogCamFra,
	title = {Visual Marker based Multi-Sensor Fusion State Estimation},
	booktitle = {20th IFAC World Congress},
	year = {2017},
	month = {07/2017},
	address = {Toulouse, France},
	abstract = {This paper presents the description and experimental results of a versatile Visual Marker based Multi-Sensor Fusion State Estimation that allows to combine a variable optional number of sensors and positioning algorithms in a loosely-coupling fashion, incorporating visual markers to increase its performances. This technique allows an aerial robot to navigate in different environments and carrying out different missions with the same state estimation architecture, exploiting the best from every sensor. The state estimation algorithm has been successfully tested controlling a quadrotor equipped with an extra IMU and a RGB camera used only to detect visual markers. The entire framework runs on an onboard computer, including the controllers and the proposed state estimator. The whole software is made publicly available to the scientific community through an open source implementation.},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2017h-SanAreTogCamFra-preprint.pdf},
	author = {Jos{\'e}-Luis-L. Sanchez-Lopez and Victor Arellano-Quintana and Marco Tognon and Pascual Campoy and Antonio Franchi}
}
