@article {cocchioni2016visual,
	title = {Visual Based Landing for an Unmanned Quadrotor},
	journal = {Journal of Intelligent \& Robotic Systems},
	volume = {84},
	number = {1-4},
	year = {2016},
	pages = {511{\textendash}528},
	publisher = {Springer Netherlands},
	author = {Francesco Cocchioni and Emanuele Frontoni and Ippoliti, Gianluca and Sauro Longhi and Adriano Mancini and Primo Zingaretti}
}
@article {Cocchioni2015,
	title = {Visual Based Landing for an Unmanned Quadrotor},
	journal = {Journal of Intelligent and Robotic Systems: Theory and Applications},
	year = {2015},
	note = {cited By 0; Article in Press},
	doi = {10.1007/s10846-015-0271-6},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84941686223\&partnerID=40\&md5=9ccfc812909e8a74b64d123902639160},
	author = {Francesco Cocchioni and Emanuele Frontoni and Ippoliti, G. and Sauro Longhi and Adriano Mancini and Primo Zingaretti}
}
@conference {Cocchioni2014418,
	title = {Autonomous navigation, landing and recharge of a quadrotor using artificial vision},
	booktitle = {2014 International Conference on Unmanned Aircraft Systems, ICUAS 2014 - Conference Proceedings},
	year = {2014},
	note = {cited By 1},
	pages = {418-429},
	abstract = {In this paper a solution to UAV reduced endurance and autonomous flight is proposed. With a complete on-board solution, based on artificial vision, the developed system is able to autonomously take off, navigate and land, recharging its battery by using a dedicated landing platform, both in indoor and outdoor scenarios. The landing platform includes a passive centering system to correct the landing error of the UAV, with a novel design wich reduce cost and increase the safety (thanks to small and isolated electrical contacts) without invasive hardware changes on the drone. The developed vision algorithm provides a fast and accurate measurement of UAV position with respect to the landing platform using a visual target, but at the same time it is able to automatically switch to an estimation of position that is independent from the visual target. This aspect is used during navigation or when the tracking of the target fails, ensuring a continuous position measurement feed to the controllers. The developed control system manages all the different phases of a mission (motor turning on/off, take off, navigation, landing,...) with low control error, ensuring a landing over the landing platform with an error that is lower than 5cm for both x and y axis. The developed software in ROS environment is modular and provides input/output interfaces to receive command, or send data. {\textcopyright} 2014 IEEE.},
	doi = {10.1109/ICUAS.2014.6842282},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84904565097\&partnerID=40\&md5=04076148a6e9b80c9da87ee06d339603},
	author = {Francesco Cocchioni and Adriano Mancini and Sauro Longhi}
}
@conference {Cocchioni2014374,
	title = {Unmanned ground and aerial vehicles in extended range indoor and outdoor missions},
	booktitle = {2014 International Conference on Unmanned Aircraft Systems, ICUAS 2014 - Conference Proceedings},
	year = {2014},
	note = {cited By 1},
	pages = {374-382},
	abstract = {The capability to instantiate a cooperation among heterogeneous agents is a fundamental feature in mobile robotics. In this paper we focus on the interaction between Unmanned Ground Vehicle (UGV) and Unmanned Aerial Vehicle (UAV) to extend the endurance of UAV, thanks to a novel landing/recharging platform. The UGV acts as a docking station and hosts the UAV during the indoor/outdoor transition and vice-versa. We designed a platform and a robust landing target to automate the fast recharge of UAV. The synchronization and coordination of cooperation is managed by a Ground Control Station (GCS) developed using a versatile software toolchain based on the integration of Stateflow, auto-generation of C-code and ROS. All the software components of UAV, UGV and GCS have been developed using ROS. The obtained results show that the UAV is able to land over the UGV with high accuracy (<5cm for both x and y axis) thanks to a visual position estimation algorithm, also in presence of wind (with gust up to 20-25km/h), recharging its batteries in a short time to extend its endurance. {\textcopyright} 2014 IEEE.},
	doi = {10.1109/ICUAS.2014.6842276},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84904582437\&partnerID=40\&md5=f57cb12575d6f9ff24ff152e95b48c80},
	author = {Francesco Cocchioni and Pierfelice, V. and Benini, A. and Adriano Mancini and Emanuele Frontoni and Primo Zingaretti and Ippoliti, G. and Sauro Longhi}
}
