@conference {2012c-CogSteFraOriBue,
	title = {3D Mutual Localization with Anonymous Bearing Measurements},
	booktitle = {2012 IEEE Int. Conf. on Robotics and Automation},
	year = {2012},
	month = {05/2012},
	address = {St. Paul, MN},
	abstract = {We present a decentralized algorithm for estimating mutual 3-D poses in a group of mobile robots, such as a team of UAVs. Our algorithm uses bearing measurements reconstructed, e.g., by a visual sensor, and inertial measurements coming from the robot IMU. Since identification of a specific robot in a group would require visual tagging and may be cumbersome in practice, we simply assume that the bear- ing measurements are anonymous. The proposed localization method is a non-trivial extension of our previous algorithm for the 2-D case, and exhibits similar performance and robustness. An experimental validation of the algorithm has been performed using quadrotor UAVs.},
	keywords = {Distributed algorithms, Estimation, Localization, Localization of aerial robots, Multi-robot systems},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2012c-CogSteFraOriBue.pdf},
	author = {Marco Cognetti and Paolo Stegagno and Antonio Franchi and Giuseppe Oriolo and Heinrich H. B{\"u}lthoff}
}
@conference {2012l-CogSteFraOri,
	title = {Two Measurement Scenarios for Anonymous Mutual Localization in Multi-UAV Systems},
	booktitle = {2nd IFAC Workshop on Multivehicle Systems},
	year = {2012},
	month = {10/2012},
	address = {Espoo, Finland},
	keywords = {Estimation, Localization, Localization of aerial robots, Multi-robot systems},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2012l-CogSteFraOri-preprint.pdf},
	author = {Marco Cognetti and Paolo Stegagno and Antonio Franchi and Giuseppe Oriolo}
}
@conference {2011m-SteCogFraOri,
	title = {Mutual Localization using Anonymous Bearing Measurements},
	booktitle = {2011 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems},
	year = {2011},
	month = {09/2011},
	pages = {469-474},
	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},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2011m-SteCogFraOri-preprint.pdf , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2011m-SteCogFraOri.mp4},
	author = {Paolo Stegagno and Marco Cognetti and Antonio Franchi and Giuseppe Oriolo}
}
@conference {2010d-FraOriSte,
	title = {Probabilistic Mutual Localization in Multi-agent Systems from Anonymous Position Measures},
	booktitle = {49th IEEE Conference on Decision and Control},
	year = {2010},
	month = {12/2010},
	pages = {6534-6540},
	address = {Atlanta, GA, USA},
	abstract = {Recent research on multi-agent systems has produced a plethora of decentralized controllers that implicitly assume various degrees of agent localization. However, many practical arrangements commonly taken to allow and achieve localization imply some form of centralization, from the use of physical tagging to allow the identification of the single agent to the adoption of global positioning systems based on cameras or GPS.
These devices clearly decrease the system autonomy and range of applicability, and should be avoided if possible. Following this guideline, this work addresses the mutual localization problem with anonymous relative position measures, presenting a robust solution based on a probabilistic framework. The proposed localization system exhibits higher accuracy and lower complexity ($O(n^2)$) than our previous method~[bib]2009c-FraOriSte[/bib].  Moreover, 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).  The proposed localization system has been validated by means of an extensive experimental study},
	keywords = {Distributed algorithms, Estimation, Localization, Multi-robot systems},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2010d-FraOriSte-preprint.pdf , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2010d-FraOriSte.pdf},
	author = {Antonio Franchi and Giuseppe Oriolo and Paolo Stegagno}
}
@conference {2010a-FraOriSte,
	title = {On the Solvability of the Mutual Localization Problem with Anonymous Position Measures},
	booktitle = {2010 IEEE Int. Conf. on Robotics and Automation},
	year = {2010},
	month = {05/2010},
	pages = {3193-3199},
	address = {Anchorage, AK},
	abstract = {This paper formulates and investigates a novel problem called Mutual Localization with Anonymous Position Measures. This is an extension of Mutual Localization with Position Measures, with the additional assumption that the identities of the measured robots are not known. A necessary and sufficient condition for the uniqueness of the solution is presented, which requires O(n^2/\log n) to be verified and is based on the notion of rotational symmetry in R^2. We also derive the relationship between the number of robots and the number of possible solutions, and classify the solutions in a number of equivalence classes which is linear in n. A control law is finally proposed that effectively breaks symmetric formations so as to guarantee unique solvability of the problem is also proposed; its performance is illustrated through simulations.},
	keywords = {Estimation, Formation control, Localization, Multi-robot systems},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2010a-FraOriSte.pdf , https://homepages.laas.fr/afranchi/robotics/sites/default/files/ICRA10-Final.mp4},
	author = {Antonio Franchi and Giuseppe Oriolo and Paolo Stegagno}
}
@conference {2009c-FraOriSte,
	title = {Mutual Localization in a Multi-Robot System with Anonymous Relative Position Measures},
	booktitle = {2009 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems},
	year = {2009},
	month = {11/2009},
	pages = {3974-3980},
	address = {St. Louis, MO},
	abstract = {We address the mutual localization problem for a multi-robot system, under the assumption that each robot is equipped with a sensor that provides a measure of the relative position of nearby robots without their identity. Anonymity generates a combinatorial ambiguity in the inversion of the measure equations, leading to a multiplicity of admissible relative pose hypotheses. To solve the problem, we propose a two-stage localization system based on MultiReg, an innovative algorithm that computes on-line all the possible relative pose hypotheses, whose output is processed by a data associator and a multiple EKF to isolate and refine the best estimates. The performance of the mutual localization system is analyzed through experiments, proving the effectiveness of the method and, in particular, its robustness with respect to false positives (objects that look like robots) and false negatives (robots that are not detected) of the measure process.},
	keywords = {Distributed algorithms, Estimation, Localization, Multi-robot systems},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2009c-FraOriSte.pdf , https://homepages.laas.fr/afranchi/robotics/sites/default/files/IROS09_MutualLoc.mp4},
	author = {Antonio Franchi and Giuseppe Oriolo and Paolo Stegagno}
}
@article {2009a-FraOriSte,
	title = {Mutual Localization in a Multi-Robot System with Anonymous Relative Position Measures},
	year = {2009},
	month = {01/2009},
	institution = {Department of Computer and System Sciences Antonio Ruberti},
	abstract = {In this paper we formulate and solve the mutual localization problem for a multi-robot system under the assumption of anonymous relative position measures. The anonymity hypothesis can cause a combinatorial ambiguity in the inversion of the measure equation giving more than one possible solution to the problem. We propose MultiReg, an innovative algorithm aimed at obtaining sets ofpossible relative pose hypotheses, whose output is processed by a data associator and a multiple EKF to select the best hypothesis. We study the performance of the developed localization system using both simulations and real robot experiments.},
	keywords = {Distributed algorithms, Estimation, Localization, Multi-robot systems},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2009a-FraOriSte.pdf},
	author = {Antonio Franchi and Giuseppe Oriolo and Paolo Stegagno}
}
