@conference {142,
	title = {Decentralized Motion Control for Cooperative Manipulation with a Team of Networked Mobile Manipulators},
	booktitle = {2016 IEEE Int. Conf. on Robotics and Automation},
	year = {2016},
	month = {05/2016},
	address = {Stockholm, Sweden},
	keywords = {Calibration of ground robots, Motion control of multiple robots},
	author = {Antonio Petitti and Antonio Franchi and Donato Di Paola and Alessandro Rizzo}
}
@article {132,
	title = {Decentralized Multi-Robot Encirclement of a 3D Target with Guaranteed Collision Avoidance},
	journal = {Autonomous Robots},
	volume = {40},
	year = {2016},
	month = {02/2016},
	pages = {245-265},
	abstract = {We present a control framework for achieving encirclement of a target moving in 3D using a multi-robot system. Three variations of a basic control strategy are proposed for different versions of the encirclement problem, and their effectiveness is formally established. An extension ensuring maintenance of a safe inter-robot distance is also discussed. The proposed framework is fully decentralized and only requires local communication among robots; in particular, each robot locally estimates all the relevant global quantities. We validate the proposed strategy through simulations on kinematic point robots and quadrotor UAVs, as well as experiments on differential-drive wheeled mobile robots.},
	keywords = {Motion control of multiple robots},
	author = {Antonio Franchi and Paolo Stegagno and Giuseppe Oriolo}
}
@article {97,
	title = {Decentralized rigidity maintenance control with range measurements for multi-robot systems},
	journal = {International Journal of Robotics Research},
	volume = {34},
	year = {2015},
	month = {01/2015},
	pages = {128},
	chapter = {105},
	abstract = {This work proposes a fully decentralized strategy for maintaining the formation rigidity of a multi-robot system using only range measurements, while still allowing the graph topology to change freely over time. In this direction, a first contribution of this work is an extension of rigidity theory to weighted frameworks and the rigidity eigenvalue, which when positive ensures the infinitesimal rigidity of the framework. We then propose a distributed algorithm for estimating a common relative position reference frame amongst a team of robots with only range measurements in addition to one agent endowed with the capability of measuring the bearing to two other agents. This first estimation step is embedded into a subsequent distributed algorithm for estimating the rigidity eigenvalue associated with the weighted framework. The estimate of the rigidity eigenvalue is finally used to generate a local control action for each agent that both maintains the rigidity property and enforces additional constraints such as collision avoidance and sensing/communication range limits and occlusions. As an additional feature of our approach, the communication and sensing links among the robots are also left free to change over time while preserving rigidity of the whole framework. The proposed scheme is then experimentally validated with a robotic testbed consisting of six quadrotor unmanned aerial vehicles operating in a cluttered environment. },
	keywords = {Decentralized control, distributed algorithm, distributed estimation, graph rigidity, multi-robot},
	doi = {10.1177/0278364914546173},
	url = {http://ijr.sagepub.com/content/34/1/105},
	author = {Daniel Zelazo and Antonio Franchi and Heinrich H. B{\"u}lthoff and Paolo Robuffo Giordano}
}
@article {135,
	title = {Distributed Pursuit-Evasion without Mapping and 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/},
	author = {Joseph W. Durham and Antonio Franchi and Francesco Bullo}
}
