@conference {Gaujens2014,
	title = {Testing of cooperative tasks for Unmanned Aerial and ground platforms},
	booktitle = {MESA 2014 - 10th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, Conference Proceedings},
	year = {2014},
	note = {cited By 0},
	abstract = {In the last years the Model Based Design for Unmanned Systems aided the safe and rational release of applications running on unmanned systems. In particular in this paper we focus on a hybrid methodology that merges Software in the Loop (SIL) and Model in the Loop (MIL) strategies for cooperative tasks performed by aerial and ground autonomous vehicles. The proposed work flow covers the design and testing of Ground Control Station (GCS) modelled by a finite state machine, the design and testing of navigation code running on UAV and UGV and the testing of cooperative missions. The work-flow is based on a realistic 3D physical simulator interfaced with Matlab-Simulink-Stafeflow. The proposed approach has been successfully tested and evaluated allowing to release runnable and safe code on real targets.},
	doi = {10.1109/MESA.2014.6935621},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84911957715\&partnerID=40\&md5=fa0db02cfc93a2552968c6a92df82cb8},
	author = {Gaujens, A. and Benini, A. 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}
}
@article {Benini2013461,
	title = {An IMU/UWB/vision-based extended kalman filter for mini-UAV localization in indoor environment using 802.15.4a wireless sensor network},
	journal = {Journal of Intelligent and Robotic Systems: Theory and Applications},
	volume = {70},
	number = {1-4},
	year = {2013},
	note = {cited By 4},
	pages = {461-476},
	abstract = {Indoor localization of mobile agents using wireless technologies is becoming very important in military and civil applications. This paper introduces an approach for the indoor localization of a mini UAV based on Ultra-WideBand technology, low cost IMU and vision based sensors. In this work an Extended Kalman Filter (EKF) is introduced as a possible technique to improve the localization. The proposed approach allows to use a low-cost Inertial Measurement Unit (IMU) in the prediction step and the integration of vision-odometry for the detection of markers nearness the touchdown area. The ranging measurements allow to reduce the errors of inertial sensors due to the limited performance of accelerometers and gyros. The obtained results show that an accuracy of 10 cm can be achieved. {\textcopyright} 2012 Springer Science+Business Media B.V.},
	doi = {10.1007/s10846-012-9742-1},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84871640127\&partnerID=40\&md5=c45e91f48415630a0fb3a388a2ca9aaa},
	author = {Benini, A. and Adriano Mancini and Sauro Longhi}
}
@conference {Benini2012735,
	title = {A Biased Extended Kalman Filter for indoor localization of a mobile agent using low-cost IMU and UWB wireless sensor network},
	booktitle = {IFAC Proceedings Volumes (IFAC-PapersOnline)},
	year = {2012},
	note = {cited By 0},
	pages = {735-740},
	abstract = {Indoor localization of mobile agents using wireless technologies is becoming very important in military and civil applications. This paper introduces an approach for the indoor localization of a mobile agent based on Ultra-WideBand technology using a Biased Extended Kalman Filter (EKF) as a possible technique to improve the localization. The proposed approach allows to use a low-cost IMU (inertial measurement unit) which performances are improved by a calibration procedure. The obtained results show that the filter allows to obtain better result in terms of localization due to the estimation of bias and scale factor. {\textcopyright} 2012 IFAC.},
	doi = {10.3182/20120905-3-HR-2030.00144},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84880993407\&partnerID=40\&md5=c8d42599e5ee04e0b909b6265235c723},
	author = {Benini, A. and Adriano Mancini and Marinelli, A. and Sauro Longhi}
}
@article {Benini2012507,
	title = {A modular framework for fast prototyping of cooperative unmanned aerial vehicle},
	journal = {Journal of Intelligent and Robotic Systems: Theory and Applications},
	volume = {65},
	number = {1-4},
	year = {2012},
	note = {cited By 4},
	pages = {507-520},
	abstract = {Unmanned Aerial Vehicles (UAVs) are gaining increasing interest thanks to their flexibility and versatility. However, these systems are very complex and a good simulation platform is needed. In this paper, a new Framework for simulation and fast prototyping of UAV control laws is presented. The Framework exploits the high realism of the simulations carried out in a three-dimensional virtual environment with the easiness of use of development systems such as Matlab{\textregistered} for fast prototyping of control systems. Then a novel method that exploits the benefits of Model Predictive Control (MPC) for cooperative scenarios is introduced. The obtained results show good performances of MPC in solving the formation problem of unmanned aerial vehicles; finding an optimal solution and taking into account different constraints. The developed framework allows also to easily change from simulated agent to real one. {\textcopyright} 2011 Springer Science+Business Media B.V.},
	doi = {10.1007/s10846-011-9577-1},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84855437595\&partnerID=40\&md5=e426704537bd52bc6397b9152f01e978},
	author = {Benini, A. and Adriano Mancini and Minutolo, R. and Sauro Longhi and Montanari, M.b}
}
@conference {Mancini2011745,
	title = {Coalition formation for unmanned quadrotors},
	booktitle = {Proceedings of the ASME Design Engineering Technical Conference},
	volume = {3},
	number = {PARTS A AND B},
	year = {2011},
	note = {cited By 1},
	pages = {745-752},
	abstract = {Today Unmanned Aerial Vehicles (UAVs) and in particular quad-rotors represent novel platforms to accomplish a wide set of missions as surveillance, Search \& Rescue, inspection, pho-togrammetry. The main limitation of these vehicles is represented by the restricted operating area. The area is mainly limited by power supplies (batteries or fuel). A strategy to overcame this limitation is to increase the number of vehicles forming a coalition. The main benefit of coalition formation are the extended mission range and the capability to increase the sensorial set. Each vehicles is a part of a dynamic network that must be properly coordinated in order to optimize all the available resources. In this paper a new framework for simulation of unmanned vehicles in cooperative scenarios is first presented. The framework is based on the interaction of a physics-engine, which simulates the dynamics of vehicles and their interaction with world increasing the realism of simulation, and a simulation environment where the high-level strategy is designed/developed. A Model Predictive Control (MPC) is then introduced to solve the problem of leader-follower applied to quad-rotors. Using the developed framework and the MPC technique is possible to easily instantiate the coalition minimizing also a cost function. The obtained results from the control strategy point of view show that positioning error at steady state is equal to zero. The MPC allows also the modelling of different conflicting constraints as the control actions, positioning error, and fuel/energy consumption. {\textcopyright} 2011 by ASME.},
	doi = {10.1115/DETC2011-48904},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84863584753\&partnerID=40\&md5=9d10818fcd0cd5219ab5df1c9eb26502},
	author = {Adriano Mancini and Benini, A. and Emanuele Frontoni and Primo Zingaretti and Sauro Longhi}
}
@conference {Benini2011406,
	title = {A simulation framework for coalition formation of Unmanned Aerial Vehicles},
	booktitle = {2011 19th Mediterranean Conference on Control and Automation, MED 2011},
	year = {2011},
	note = {cited By 3},
	pages = {406-411},
	abstract = {Unmanned Aerial Vehicles (UAVs) and in particular quad-rotors are gaining an increasing interest owing to their flexibility and versatility. Today the challenge is to integrate these versatile platforms in a wide fleet in order to perform cooperative tasks as surveillance, search \& rescue, inspection. The coalition formation problem is a pre-condition for cooperative missions. This problem can be solved with different methodologies from biologically-inspired algorithms to parasocial consensus sampling ones. In this paper a new framework for simulation of unmanned vehicles in cooperative scenarios is first presented. Then a novel method that exploits the benefits of Model Predictive Control (MPC) for a coalition formation problem (leader-follower) is introduced. The obtained results evidence the good performance of MPC to solve the problem of coalition formation for unmanned aerial vehicles finding the optimal solution taking into account different kind of constraints. The developed framework allows also to easily change from simulated agent to real one. {\textcopyright} 2011 IEEE.},
	doi = {10.1109/MED.2011.5983163},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-80052355021\&partnerID=40\&md5=51acc4875190b250928b66e5b54b01a0},
	author = {Benini, A. and Adriano Mancini and Emanuele Frontoni and Primo Zingaretti and Sauro Longhi}
}
