@conference {Alhafnawi2022,
	title = {MOSAIX: a Swarm of Robot Tiles for Social Human-Swarm Interaction},
	booktitle = {2022 International Conference on Robotics and Automation (ICRA)},
	year = {2022},
	pages = {6882-6888},
	doi = {10.1109/ICRA46639.2022.9811723},
	author = {M Alhafnawi and E R Hunt and S Lemaignan and P O{\textquoteright}Dowd and S Hauert}
}
@article {468,
	title = {Multi-robot search for a stationary object placed in a known environment with a combination of GRASP and VND},
	journal = {International Transactions in Operational Research},
	volume = {29},
	year = {2022},
	pages = {805-836},
	doi = {10.1111/itor.12794},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/itor.12794},
	author = {Kulich, Miroslav and P{\v r}eu{\v c}il, Libor}
}
@article {411,
	title = {Multi-robot online sensing strategies for the construction of communication maps},
	journal = {Autonomous Robots},
	volume = {44},
	year = {2020},
	month = {Jan-03-2020},
	pages = {299 - 319},
	abstract = {This paper tackles the problem of constructing a communication map of a known environment using multiple robots. A communication map encodes information on whether two robots can communicate when they are at two arbitrary locations and plays a fundamental role for a multi-robot system deployment to reliably and effectively achieve a variety of tasks, such as environmental monitoring and exploration. Previous work on communication map building typically considered only scenarios with a fixed base station and designed offline methods, which did not exploit data collected online by the robots. This paper proposes Gaussian Process-based online methods to efficiently build a communication map with multiple robots. Such robots form a mesh network, where there is no fixed base station. Specifically, we provide two leader-follower online sensing strategies to coordinate and guide the robots while collecting data. Furthermore, we improve the performance and computational efficiency by exploiting prior communication models that can be built from the physical map of the environment. Extensive experimental results in simulation and with a team of TurtleBot 2 platforms validate the approach.},
	keywords = {Communication maps, Multi-robot systems, Sensing strategies},
	issn = {0929-5593},
	doi = {10.1007/s10514-019-09862-3},
	url = {http://link.springer.com/10.1007/s10514-019-09862-3},
	author = {Quattrini~Li, Alberto and Penumarthi, Phani Krishna and Banfi, Jacopo and Basilico, Nicola and O{\textquoteright}Kane, Jason M. and Rekleitis, Ioannis and Nelakuditi, Srihari and Amigoni, Francesco}
}
@article {399,
	title = {A Multi-Trip Task Assignment for Early Target Inspection in Squads of Aerial Drones},
	journal = {IEEE Transactions on Mobile Computing},
	volume = {in press},
	year = {2020},
	author = {N. Bartolini and Andrea Coletta and Gaia Maselli and Ala Khalifeh}
}
@article {301,
	title = {Markov inequality rule for switching among time optimal controllers in a multiple vehicle intercept problem},
	journal = {Automatica},
	volume = {87},
	year = {2018},
	pages = {274--280},
	doi = {https://doi.org/10.1016/j.automatica.2017.09.009},
	url = {https://www.sciencedirect.com/science/article/pii/S000510981730479X?via\%3Dihub},
	author = {Dejan Milutinovi{\'c} and David W. Casbeer and Meir Pachter}
}
@conference {375,
	title = {Multi-Agent Path Finding with Deadlines},
	booktitle = {International Joint Conference on Artificial Intelligence (IJCAI)},
	year = {2018},
	keywords = {conference},
	author = {Hang Ma and Glenn Wagner and Ariel Felner and Jiaoyang Li and T. K. Satish Kumar and Sven Koenig}
}
@conference {376,
	title = {Multi-Agent Path Finding with Deadlines: Preliminary Results},
	booktitle = {International Conference on Autonomous Agents and Multiagent Systems (AAMAS)},
	year = {2018},
	author = {Hang Ma and Glenn Wagner and Ariel Felner and Jiaoyang Li and T. K. Satish Kumar and Sven Koenig}
}
@conference {417,
	title = {Multi-robot Dubins Coverage with Autonomous Surface Vehicles},
	booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
	year = {2018},
	url = {https://doi.org/10.1109/ICRA.2018.8460661},
	author = {Nare Karapetyan and Jason Moulton and Jeremy S. Lewis and Quattrini~Li, Alberto and Jason M. O{\textquoteright}Kane and Ioannis Rekleitis}
}
@conference {379,
	title = {Multi-Agent Path Finding with Delay Probabilities},
	booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
	year = {2017},
	keywords = {conference},
	author = {Hang Ma and T. K. Satish Kumar and Sven Koenig}
}
@conference {332,
	title = {Multirobot Exploration for Building Communication Maps with Prior from Communication Models},
	booktitle = {Proceedings of the International Symposium on Multi-Robot and Multi-Agent Systems (MRS)},
	year = {2017},
	author = {Phani Krishna Penumarthi and Quattrini~Li, Alberto and Jacopo Banfi and Nicola Basilico and Francesco Amigoni and Jason O{\textquoteright}Kane and Ioannis Rekleitis and Srihari Nelakuditi}
}
@conference {333,
	title = {Multirobot Online Construction of Communication Maps},
	booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)},
	year = {2017},
	abstract = {The importance of communication in many multirobot information-gathering tasks requires the availability of reliable communication maps. These provide estimates of the radio signal strength and can be used to predict the presence of communication links between different locations of the environment. In the problem we consider, a team of mobile robots has to build such maps autonomously in a robot-to-robot communication setting. The solution we propose models the signal{\textquoteright}s distribution with a Gaussian Process and exploits different online sensing strategies to coordinate and guide the robots during their data acquisition. Our methods show interesting operative insights both in simulations and on real TurtleBot 2 platforms.},
	doi = {10.1109/ICRA.2017.7989300},
	author = {Jacopo Banfi and Quattrini~Li, Alberto and Nicola Basilico and Ioannis Rekleitis and Francesco Amigoni}
}
@article {370,
	title = {Multirobot Systems [TC Spotlight]},
	journal = {IEEE Robotics \& Automation Magazine},
	volume = {24},
	year = {2017},
	month = {Jan-06-2017},
	pages = {12 - 16},
	issn = {1070-9932},
	doi = {10.1109/MRA.2017.2691138},
	url = {http://ieeexplore.ieee.org/document/7947267/http://xplorestaging.ieee.org/ielx7/100/7947233/07947267.pdf?arnumber=7947267},
	author = {Ayanian, Nora and Fitch, Robert and Franchi, Antonio and Sabattini, Lorenzo}
}
@article {165,
	title = {Model and analysis of the interaction dynamics in cooperative manipulation tasks},
	journal = {IEEE Transactions on Robotics (T-RO), accepted},
	year = {2016},
	url = {https://mediatum.ub.tum.de/doc/1276284/132134.pdf},
	author = {S. Erhart and S. Hirche}
}
@conference {188,
	title = {Multi-Agent Path Finding with Kinematic Constraints},
	booktitle = {International Conference on Automated Planning and Scheduling},
	year = {2016},
	month = {Jun},
	address = {London, UK},
	keywords = {Multi-Agent Path Finding with Kinematic Contraints},
	author = {Wolfgang H{\"o}nig and T. K. Satish Kumar and Liron Cohen and Hang Ma and Hong Xu and Nora Ayanian and Sven Koenig}
}
@conference {382,
	title = {Multi-Agent Path Finding with Payload Transfers and the Package-Exchange Robot-Routing Problem},
	booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
	year = {2016},
	keywords = {conference},
	author = {Hang Ma and Craig Tovey and Guni Sharon and T. K. Satish Kumar and Sven Koenig}
}
@conference {212,
	title = {Minimizing communication latency in multirobot situation-aware patrolling},
	booktitle = {Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on},
	year = {2015},
	publisher = {IEEE},
	organization = {IEEE},
	author = {Banfi, Jacopo and Basilico, Nicola and Amigoni, Francesco}
}
@conference {359,
	title = {A mixed integer programming model for timed deliveries in multirobot systems},
	booktitle = {2015 IEEE International Conference on Automation Science and Engineering (CASE)2015 IEEE International Conference on Automation Science and Engineering (CASE)},
	year = {2015},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Gothenburg, Sweden},
	doi = {10.1109/CoASE.2015.7294146},
	url = {http://ieeexplore.ieee.org/document/7294146/http://xplorestaging.ieee.org/ielx7/7279855/7294025/07294146.pdf?arnumber=7294146},
	author = {Kamra, Nitin and Ayanian, Nora}
}
@conference {360,
	title = {Mixed reality for robotics},
	booktitle = {2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
	year = {2015},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Hamburg, Germany},
	doi = {10.1109/IROS.2015.7354138},
	url = {http://ieeexplore.ieee.org/document/7354138/http://xplorestaging.ieee.org/ielx7/7347169/7353104/07354138.pdf?arnumber=7354138},
	author = {Honig, Wolfgang and Milanes, Christina and Scaria, Lisa and Phan, Thai and Bolas, Mark and Ayanian, Nora}
}
@conference {192,
	title = {Mixed Reality for Robotics},
	booktitle = {IEEE/RSJ Intl Conf. Intelligent Robots and Systems},
	year = {2015},
	month = {Sept},
	address = {Hamburg, Germany},
	author = {Wolfgang Hoenig and Christina Milanes and Lisa Scaria and Thai Phan and Mark Bolas and Nora Ayanian}
}
@conference {159,
	title = {Multi-robot manipulation controlled by a human with haptic feedback},
	booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
	year = {2015},
	abstract = {The interaction of a single human with a team of cooperative robots, which collaboratively manipulate an object, poses a great challenge by means of the numerous possibilities of issuing commands to the team or providing appropriate feedback to the human. In this paper we propose a formationbased approach in order to avoid deformations of the object and to virtually couple the human to the formation. Here the human can be interpreted as a leader in a leader-follower formation with the robotic manipulators being the followers. The results of a controllability analysis in such a leader-follower formation suggest that it is beneficial to measure the state of the human (leader) by all physically cooperating manipulators (followers). The proposed approach is evaluated in a full-scale multi-robot cooperative manipulation experiment with humans.},
	author = {D. Sieber and S. Music and S. Hirche}
}
@article {215,
	title = {A Multirobot System for Distributed Area Coverage and Signal Searching in Large Outdoor Scenarios},
	journal = {Journal of Field Robotics},
	year = {2015},
	pages = {n/a{\textendash}n/a},
	issn = {1556-4967},
	doi = {10.1002/rob.21636},
	url = {http://dx.doi.org/10.1002/rob.21636},
	author = {Garz{\'o}n, Mario and Valente, Jo{\~a}o and Rold{\'a}n, Juan Jes{\'u}s and Cancar, Leandro and Barrientos, Antonio and Del Cerro, Jaime}
}
@article {nair2015multisatellite,
	title = {Multisatellite Formation Control for Remote Sensing Applications Using Artificial Potential Field and Adaptive Fuzzy Sliding Mode Control},
	journal = {IEEE Systems Journal},
	volume = {9},
	number = {2},
	year = {2015},
	pages = {508{\textendash}518},
	publisher = {IEEE Systems Journal},
	author = {Nair, Ranjith Ravindranathan and Behera, Laxmidhar and Kumar, Vinod and Jamshidi, Mo}
}
@article {197,
	title = {Mechanism and Convergence Analysis of a Multi-Robot Swarm Approach Based on Natural Selection},
	journal = {Journal of Intelligent and Robotic Systems},
	volume = {76},
	year = {2014},
	month = {Nov.},
	pages = {353-381},
	author = {Couceiro, M S and Martins, F M and Rocha, R P and Ferreira, N M F}
}
@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 {204,
	title = {Multi-Robot Patrolling Algorithms: Examining Performance and Scalability},
	journal = {Advanced Robotics},
	volume = {27},
	year = {2013},
	pages = {325-336},
	author = {D. Portugal and R.P. Rocha}
}
@conference {42,
	title = {Multi-UAV Motion Planning for Guaranteed Search},
	booktitle = {Proc. of the 12th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2013)},
	year = {2013},
	address = {St. Paul, MN, USA},
	abstract = {We consider the problem of detecting all moving and evading targets in 2.5D environments with teams of UAVs. Targets are assumed to be fast and omniscient while UAVs are only equipped with limited range detection sensors and have no prior knowledge about the location of targets. We present an algorithm that, given an elevation map of the environment, computes synchronized trajectories for the UAVs to guarantee the detection of all targets. The approach is based on coordinating the motion of multiple UAVs on sweep lines to clear the environment from contamination, which represents the possibility of an undetected target being located in an area. The goal is to compute trajectories that minimize the number of UAVs needed to execute the guaranteed search. This is achieved by converting 2D strategies, computed for a polygonal representation of the environment, to 2.5D strategies. We present methods for this conversion and consider cost of motion and visibility constraints. Experimental results demonstrate feasibility and scalability of the approach. Experiments are carried out on real and artificial elevation maps and provide the basis for future deployments of large teams of real UAVs for guaranteed search.},
	keywords = {guaranteed search, multi-robot, multi-UAV, pursuit-evasion},
	isbn = {978-1-4503-1993-5},
	url = {http://dl.acm.org/citation.cfm?id=2484920.2484936},
	author = {A. Kolling and A. Kleiner}
}
@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 {49,
	title = {A Mechanism for Dynamic Ride Sharing based on Parallel Auctions},
	booktitle = {Proc. of the 22th International Joint Conference on Artificial Intelligence (IJCAI)},
	year = {2011},
	address = {Barcelona, Spain},
	abstract = {Car pollution is one of the major causes of green- house emissions, and traffic congestion is rapidly becoming a social plague. Dynamic Ride Sharing (DRS) systems have the potential to mitigate this problem by computing plans for car drivers, e.g. commuters, allowing them to share their rides. Ex- isting efforts in DRS are suffering from the problem that participants are abandoning the system after repeatedly failing to get a shared ride. In this paper we present an incentive compatible DRS solution based on auctions. While existing DRS systems are mainly focusing on fixed assignments that minimize the totally travelled distance, the presented approach is adaptive to individual preferences of the participants. Furthermore, our system allows to tradeoff the minimization of Vehicle Kilometers Travelled (VKT) with the overall probability of successful ride-shares, which is an important feature when bootstrapping the system. To the best of our knowledge, we are the first to present a DRS solution based on auctions using a sealed-bid second price scheme.},
	isbn = {978-1-57735-516-8},
	author = {Kleiner, A. and Nebel, B. and Ziparo, V.}
}
@conference {ravindranathan2011multi,
	title = {Multi-Agent Formation Control using Adaptive Fuzzy Sliding Mode Control},
	booktitle = {International UKIERI workshop on Brain computer Interface and assistive robotics, July 2011,University of Ulster, UK.},
	year = {2011},
	author = {Ravindranathan Nair, Ranjith and Behera, Laxmidhar}
}
@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}
}
@article {180,
	title = {Multiple Traveling Robot Problem: A Solution Based on Dynamic Task Selection and Robust Execution},
	journal = {Mechatronics, IEEE/ASME Transactions on},
	volume = {14},
	year = {2009},
	pages = {198-206},
	keywords = {Distributed multirobot task allocation, dynamic task selection scheme, incremental task allocation, incremental task selection, mobile robots, Multi-robot systems, multiple traveling robot problem, multiple traveling robot problem (MTRP), NP-hard multiple traveling salesman problem, path planning, priority-based rough schedules, Robust Control, robust execution, robustness, travelling salesman problems},
	issn = {1083-4435},
	doi = {10.1109/TMECH.2009.2014157},
	author = {Sanem Sariel-Talay and Tucker R. Balch and Nadia Erdogan}
}
@article {152,
	title = {Modeling and Optimal Centralized Control of a Large-Size Robotic Population},
	journal = {IEEE Transactions on Robotics},
	volume = {22},
	year = {2006},
	month = {12/2006},
	pages = {1280-1285},
	author = {Dejan Milutinovi{\'c} and Pedro Lima}
}
@conference {ranjith2006modeling,
	title = {Modeling drag Optimal Configuration of Aircrafts in Formation},
	booktitle = {NCTT},
	year = {2006},
	pages = {111{\textendash}116},
	author = {Ranjith, R and Rajeev, U. P. and Pai, A. Dinesh}
}
