@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 {2011q-SonFraChuKimBueRob,
	title = {Human-Centered Design and Evaluation of Haptic Cueing for Teleoperation of Multiple Mobile Robots},
	journal = {IEEE Transactions on Systems, Man, \& Cybernetics. Part B: Cybernetics},
	volume = {43},
	year = {2013},
	month = {04/2013},
	pages = {597-609},
	abstract = {In this paper, we investigate the effect of haptic cueing on human operator{\textquoteright}s performance in the field of bilateral teleoperation of multiple mobile robots, in particular multiple unmanned aerial vehicles (UAVs). Two aspects of human performance are deemed important in this area, namely the maneuverability of mobile robots and perceptual sensitivity of the remote environment. We introduce metrics that allow us to address these aspects in two psychophysical studies, which are reported here. Three fundamental haptic cue types were evaluated. The Force cue conveys information on the proximity of the commanded trajectory to obstacles in the remote environment. The Velocity cue represents the mismatch between the commanded and actual velocity of the UAVs and can implicitly provide a rich amount of information regarding the actual behavior of the UAVs. Finally, the Velocity+Force cue is a linear combination of the two.
Our experimental results show that while maneuverability is best supported by the Force cue feedback, perceptual sensitivity is best served by the Velocity cue feedback. In addition, we show that large gains in the haptic feedbacks do not always guarantee an enhancement in teleoperator{\textquoteright}s performance.},
	keywords = {Evaluation, Force feedback, Haptics, Multi-robot systems, Psychophysical evaluation of haptic feedback, Psychophysics, Teleoperation},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2013a-SonFraChuKimBueRob_1.pdf},
	author = {Hyoung Il Son and Antonio Franchi and Lewis L. Chuang and Junsuk Kim and Heinrich H. B{\"u}lthoff and Paolo Robuffo Giordano}
}
@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}
}
@article {2011c-DurFraBul,
	title = {Distributed Pursuit-Evasion without Mapping or Global Localization via Local Frontiers},
	journal = {Autonomous Robots},
	volume = {32},
	year = {2012},
	month = {01/2012},
	pages = {81-95},
	abstract = {This paper addresses a visibility-based pursuit-evasion problem in which a team of mobile robots with limited sensing and communication capabilities must coordinate to detect any evaders in an unknown, multiply-connected planar environment. Our distributed algorithm to guarantee evader detection is built around maintaining complete coverage of the frontier between cleared and contaminated regions while expanding the cleared region. We detail a novel distributed method for storing and updating this frontier without building a map of the environment or requiring global localization. We demonstrate the functionality of the algorithm through simulations in realistic environments and through hardware experiments. We also compare Monte Carlo results for our algorithm to the theoretical optimum area cleared as a function of the number of robots available.},
	keywords = {Coverage, Distributed algorithms, Multi-robot systems, Pursuit-evasion / Clearing},
	url = {http://www.springerlink.com/content/a02pr41790ll754w/},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2011c-DurFraBul-preprint.pdf , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2011c-DurFraBul-video1.mp4},
	author = {Joseph W. Durham and Antonio Franchi and Francesco Bullo}
}
@conference {2011d-SonKimChuFraRobLeeBue,
	title = {An Evaluation of Haptic Cues on the Tele-Operator{\textquoteright}s Perceptual  Awareness of Multiple UAVs{\textquoteright} Environments},
	booktitle = { IEEE  World Haptics Conference},
	year = {2011},
	month = {06/2011},
	pages = {149-154},
	address = {Istanbul, Turkey},
	abstract = {The use of multiple unmanned aerial vehicles (UAVs) is increasingly being incorporated into a wide range of teleoperation applications. To date, relevant research has largely been focused on the development of appropriate control schemes. In this paper, we extend previous research by investigating how control performance could be improved by providing the teleoperator with haptic feedback cues. First, we describe a control scheme that allows a teleoperator to manipulate the flight of multiple UAVs in a remote environment. Next, we present three designs of haptic cue feedback that could increase the teleoperator{\textquoteright}s environmental awareness of such a remote environment. These cues are based on the UAVs{\textquoteright} i) velocity information, ii) proximity to obstacles, and iii) a combination of these two sources of information. Finally, we present an experimental evaluation of these haptic cue designs. Our evaluation is based on the teleoperator{\textquoteright}s perceptual sensitivity to the physical environment inhabited by the multiple UAVs. We conclude that a teleoperator{\textquoteright}s perceptual sensitivity is best served by haptic feedback cues that are based on the velocity information of multiple UAVs.},
	keywords = {Evaluation, Force feedback, Haptics, Multi-robot systems, Psychophysics, Teleoperation},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2011d-SonKimChuFraRobLeeBue-preprint.pdf},
	author = {Hyoung Il Son and Junsuk Kim and Lewis L. Chuang and Antonio Franchi and Paolo Robuffo Giordano and Dongjun Lee and Heinrich H. B{\"u}lthoff}
}
@conference {2011h-SonChuFraKimLeeLeeBueRob,
	title = {Measuring an Operator{\textquoteright}s Maneuverability Performance in the Haptic Teleoperation of Multiple Robots},
	booktitle = {2011 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems},
	year = {2011},
	month = {09/2011},
	pages = {3039-3046},
	address = {San Francisco, CA},
	abstract = {In this paper, we investigate the maneuverability performance of human teleoperators on multi-robots. First, we propose that maneuverability performance can be assessed by a frequency response function that jointly considers the input force of the operator and the position errors of the multi-robot system that is being maneuvered. Doing so allows us to evaluate maneuverability performance in terms of the human teleoperator{\textquoteright}s interaction with the controlled system. This allowed us to effectively determine the suitability of different haptic cue algorithms in improving teleoperation maneuverability. Performance metrics based on the human teleoperator{\textquoteright}s frequency response function indicate that maneuverability performance is best supported by a haptic feedback algorithm which is based on an obstacle avoidance force.},
	keywords = {Evaluation, Force feedback, Haptics, Multi-robot systems, Psychophysics, Teleoperation},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2011h-SonChuFraKimLeeLeeBueRob-preprint.pdf},
	author = {Hyoung Il Son and Lewis L. Chuang and Antonio Franchi and Junsuk Kim and Dongjun Lee and Seong-Whan Lee and Heinrich H. B{\"u}lthoff and Paolo Robuffo Giordano}
}
@conference {2010b-DurFraBul,
	title = {Distributed Pursuit-Evasion with Limited-Visibility Sensor Via Frontier-based Exploration},
	booktitle = {2010 IEEE Int. Conf. on Robotics and Automation},
	year = {2010},
	month = {05/2010},
	pages = {3562-3568},
	address = {Anchorage, AK},
	abstract = {This paper addresses a novel visibility-based pursuit-evasion problem in which a team of searchers with limited range sensors must coordinate to clear any evaders from an unknown planar environment. We present a distributed algorithm built around guaranteeing complete coverage of the frontier between cleared and contaminated areas while expanding the cleared area. Our frontier-based algorithm can guarantee detection of evaders in unknown, multiply-connected planar environments which may be non-polygonal. We also detail a method for storing and updating the global frontier between cleared and contaminated areas without building a global map or requiring global localization, which enables our algorithm to be truly distributed. We demonstrate the functionality of the algorithm through Player/Stage simulations. },
	keywords = {Coverage, Distributed algorithms, Multi-robot systems, Pursuit-evasion / Clearing},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2010b-DurFraBul.pdf , https://homepages.laas.fr/afranchi/robotics/sites/default/files/ICRA10-FinalSub.mp4},
	author = {Joseph W. Durham 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}
}
