@article {2017k-NesRobBueFra,
	title = {Decentralized Simultaneous Multi-target Exploration using a Connected Network of Multiple Robots},
	journal = {Autonomous Robots},
	volume = {41},
	year = {2017},
	month = {03/2016},
	pages = {989-1011},
	abstract = {This paper presents a novel decentralized control strategy for a multi-robot system that enables parallel multi-target exploration while ensuring a time-varying connected topology in cluttered 3D environments. Flexible continuous connectivity is guaranteed by building upon a recent connectivity maintenance method, in which limited range, line-of-sight visibility, and collision avoidance are taken into account at the same time.
Completeness of the decentralized multi-target exploration algorithm is guaranteed by dynamically assigning the robots with different motion behaviors during the exploration task. One major group is subject to a suitable downscaling of the main traveling force based on the traveling efficiency of the current leader and the direction alignment between traveling and connectivity force. This supports the leader in always reaching its current target and, on a larger time horizon, that the whole team realizes the overall task in finite time.
Extensive Monte~Carlo simulations with a group of several quadrotor UAVs show the scalability and effectiveness of the proposed method and experiments validate its practicability. },
	keywords = {Connectivity maintenance, Exploration, Motion control of multiple robots, Patrolling / Surveillance},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/1505.05441v3.pdf , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2016g-NesRobBueFra-exp.mp4 , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2016g-NesRobBueFra-empty.mp4 , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2016g-NesRobBueFra-office.mp4 , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2016g-NesRobBueFra-town.mp4},
	author = {Thomas Nestmeyer and Paolo Robuffo Giordano and Heinrich H. B{\"u}lthoff and Antonio Franchi}
}
@conference {2014g-GagOriBueFra,
	title = {Image-based Road Network Clearing without Localization and without Maps using a Team of UAVs},
	booktitle = {2014 European Control Conference},
	year = {2014},
	month = {06/2014},
	pages = {1902-1908},
	address = {Strasbourg, France},
	abstract = {We address the problem of clearing an arbitrary and unknown network of roads using an organized team of Unmanned Aerial Vehicles (UAVs) equipped with a monocular down-facing camera, an altimeter, plus high-bandwidth short- range and low-bandwidth long-range communication systems. We allow the UAVs to possibly split in several subgroups. In each subgroup a leader guides the motion employing a hierarchical coordination. A feature/image-based algorithm guides the subgroup toward the unexplored region without any use of global localization or environmental mapping. At the same time all the entry-points of the the explored region are kept under control, so that any moving object that enters or exits the previously cleared area. Simulative results on real aerial images demonstrate the functionalities and the effectiveness of the proposed algorithm. },
	keywords = {Aerial Robotics, Exploration, Motion control of multiple robots, Patrolling / Surveillance, Pursuit-evasion / Clearing},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2014g-GagOriBueFra-preprint.pdf , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2014g-GagOriBueFra-video.mp4},
	author = {Matteo Gagliardi and Giuseppe Oriolo and Heinrich H. B{\"u}lthoff and Antonio Franchi}
}
@article {2010f-FraPasBul,
	title = {On Cooperative Patrolling: Optimal Trajectories, Complexity Analysis, and Approximation Algorithms},
	journal = {IEEE Transaction on Robotics},
	volume = {28},
	year = {2012},
	month = {06/2012},
	pages = {592-606},
	abstract = {The subject of this work is the patrolling of an environment with the aid of a team of autonomous agents. We consider both the design of open-loop trajectories with optimal properties, and of distributed control laws converging to optimal trajectories. As performance criteria, the refresh time and the latency are considered, i.e., respectively, time gap between any two visits of the same region, and the time necessary to inform every agent about an event occurred in the environment. We associate a graph with the environment, and we study separately the case of a chain, tree, and cyclic graph. For the case of chain graph, we first describe a minimum refresh time and latency team trajectory, and we propose a polynomial time algorithm for its computation. Then, we describe a distributed procedure that steers the robots toward an optimal trajectory. For the case of tree graph, a polynomial time algorithm is developed for the minimum refresh time problem, under the technical assumption of a constant number of robots involved in the patrolling task. Finally, we show that the design of a minimum refresh time trajectory for a cyclic graph is NP-hard, and we develop a constant factor approximation algorithm.},
	keywords = {Coverage, Distributed algorithms, Multi-robot systems, Patrolling / Surveillance},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2010f-FraPasBul-preprint.pdf},
	author = {Fabio Pasqualetti and Antonio Franchi and Francesco Bullo}
}
@conference {2010e-PasFraBul,
	title = {On Optimal Cooperative Patrolling},
	booktitle = {49th IEEE Conference on Decision and Control},
	year = {2010},
	month = {12/2010},
	pages = {7153-7158},
	address = {Atlanta, GA, USA},
	abstract = {This work considers the problem of designing optimal multi-agent trajectories to patrol an environment. As performance criterion for optimal patrolling we consider the worst-case time gap between any two visits of the same region. We represent the area to be patrolled with a graph, and we characterize the computational complexity of the trajectory design (patrolling) problem with respect to the environment topology and to the number of robots employed in the patrolling task. Even though the patrolling problem is generally NP-hard, we identify particular cases that are solvable efficiently, and we describe optimal patrolling trajectories. Finally, we present a heuristic with performance guarantees, and an 8-approximation algorithm to solve the NP-hard patrolling problem.},
	keywords = {Coverage, Distributed algorithms, Multi-robot systems, Patrolling / Surveillance},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2010e-PasFraBul-preprint.pdf , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2010e-PasFraBul.pdf},
	author = {Fabio Pasqualetti and Antonio Franchi and Francesco Bullo}
}
@mastersthesis {60,
	title = {Decentralized Methods for Cooperative Task  Execution in Multi-robot Systems},
	year = {2009},
	month = {12/2009},
	school = {"La Sapienza" University of Rome},
	type = {PhD},
	keywords = {Coverage, Decentralized control, Distributed algorithms, Estimation, Exploration, Formation control, Localization of ground robots, Middleware for robotics, Motion control of multiple robots, Multi-robot systems, Patrolling / Surveillance, Pursuit-evasion / Clearing},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2009-Franchi_PhDThesis.pdf},
	author = {Antonio Franchi}
}
