@conference {144,
	title = {Multi-Target Visual Tracking with UAVs},
	booktitle = {2014 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems},
	year = {2014},
	month = {09/2014},
	address = {Chicago, IL},
	abstract = {We study the problem of tracking mobile targets using a team of aerial robots. Each robot carries a camera to detect targets moving on the ground. The overall goal is to plan for the trajectories of the robots in order to track the most number of targets, and accurately estimate the target locations using the images. The two objectives can conflict since a robot may fly to a higher altitude and potentially cover a larger number of targets at the expense of accuracy. We start by showing that k >= 3 robots may not be able to track all n targets while maintaining a constant factor approximation of the optimal quality of tracking at all times. Next, we study the problem of choosing robot trajectories to maximize either the number of targets tracked or the quality of tracking. We formulate this problem as the weighted version of a combinatorial optimization problem known as the Maximum Group Coverage (MGC) problem. A greedy algorithm yields a 1/2 approximation for the weighted MGC problem. Finally, we evaluate the algorithm and the sensing model through simulations and preliminary experiments.},
	author = {Pratap Tokekar and Volkan Isler and Antonio Franchi}
}
@article {136,
	title = {Mutual Localization in Multi-Robot Systems using Anonymous Relative Measurements},
	journal = {The International Journal of Robotics Research},
	volume = {32},
	year = {2013},
	month = {09/2013},
	pages = {1303-1322},
	abstract = {We propose a decentralized method to perform mutual localization in multi-robot systems using anonymous relative measurements, i.e., measurements that do not include the identity of the measured robot. This is a challenging and practically relevant operating scenario that has received little attention in the literature. Our mutual localization algorithm includes two main components: a probabilistic multiple registration stage, which provides all data associations that are consistent with the relative robot measurements and the current belief, and a dynamic filtering stage, which incorporates odometric data into the estimation process. The design of the proposed method proceeds from a detailed formal analysis of the implications of anonymity on the mutual localization problem. Experimental results on a team of differential-drive robots illustrate the effectiveness of the approach, and in particular its robustness against false positives and negatives that may affect the robot measurement process. We also provide an experimental comparison that shows how the proposed method outperforms more classical approaches that may be designed building on existing techniques. The source code of the proposed method is available within the MLAM ROS stack.},
	keywords = {Localization of ground robots},
	author = {Antonio Franchi and Giuseppe Oriolo and Paolo Stegagno}
}
@article {35,
	title = {Modeling and Control of UAV Bearing-Formations with Bilateral High-Level Steering},
	journal = {The International Journal of Robotics Research, Special Issue on 3D Exploration, Mapping, and Surveillance},
	volume = {31},
	year = {2012},
	month = {10/2012},
	pages = {1504-1525},
	abstract = {In this paper we address the problem of controlling the motion of a group of UAVs bound to keep a formation defined in terms of only relative angles (i.e., a bearing-formation). This problem can naturally arise within the context of several multi-robot applications such as, e.g., exploration, coverage, and surveillance. First, we introduce and thoroughly analyze the concept and properties of bearing-formations, and provide a class of minimally linear sets of bearings sufficient to uniquely define such formations. We then propose a bearing-only formation controller requiring only bearing measurements, converging almost globally, and maintaining bounded inter-agent distances despite the lack of direct metric information. The controller still leaves the possibility to impose group motions tangent to the current bearing-formation. These can be either autonomously chosen by the robots because of any additional task (e.g., exploration), or exploited by an assisting human co-operator. For this latter {\textquoteleft}human-in-the-loop{\textquoteright} case, we propose a multi-master/multi-slave bilateral shared control system providing the co-operator with some suitable force cues informative of the UAV performance. The proposed theoretical framework is extensively validated by means of simulations and experiments with quadrotor UAVs equipped with onboard cameras. Practical limitations, e.g., limited field-of-view, are also considered.},
	keywords = {Bilateral Shared Control of Mobile Robots, Decentralized control, Force feedback, Formation control, Haptics, Motion control of multiple robots, Multi-robot systems, Teleoperation},
	author = {Antonio Franchi and Carlo Masone and Volker Grabe and Markus Ryll and Heinrich H. B{\"u}lthoff and Paolo Robuffo Giordano}
}
@conference {145,
	title = {Mutual Localization using Anonymous Bearing Measurements},
	booktitle = {2011 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems},
	year = {2011},
	month = {09/2011},
	address = {San Francisco, CA},
	abstract = {This paper addresses the problem of mutual localization in multi-robot systems in presence of anonymous (i.e., without the identity information) bearing-only measurements. The solution of this problem is relevant for the design and implementation of any decentralized multi-robot algorithm/control. A novel algorithm for probabilistic multiple registration of these measurements is presented, where no global localization, distances, or identity are used. With respect to more conventional solutions that could be conceived on the basis of the current literature, our method is theoretically suitable for tasks requiring frequent, many-to-many encounters among agents (e.g., formation control, cooperative exploration, multiple-view environment sensing). An extensive experimental study validates our method and compares it with the fullinformative case of bearing plus-distance measurements. The results show that the proposed localization system exhibits an accuracy commensurate to our previous method [1] which uses bearing-plus-distance information.},
	keywords = {Distributed algorithms, Estimation, Localization, Multi-robot systems},
	author = {Paolo Stegagno and Marco Cognetti and Antonio Franchi and Giuseppe Oriolo}
}
