@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}
}
@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}
}
