@article {Hunt2020,
	title = {A checklist for safe robot swarms},
	journal = {Nature Machine Intelligence},
	volume = {2},
	year = {2020},
	pages = {420-422},
	abstract = {As robot swarms move from the laboratory to real-world applications, a routine checklist of questions could help ensure their safe operation.},
	issn = {2522-5839},
	doi = {10.1038/s42256-020-0213-2},
	url = {https://doi.org/10.1038/s42256-020-0213-2},
	author = {Edmund R Hunt and Sabine Hauert}
}
@conference {493,
	title = {A Connectivity-Prediction Algorithm and its Application in Active Cooperative Localization for Multi-Robot Systems},
	booktitle = {2020 IEEE International Conference on Robotics and Automation (ICRA)},
	year = {2020},
	doi = {10.1109/ICRA40945.2020.9197083},
	author = {Zhang, Liang and Zhang, Zexu and Siegwart, Roland and Chung, Jen Jen}
}
@article {352,
	title = {Combinatorial Problems in Multirobot Battery Exchange Systems},
	journal = {IEEE Transactions on Automation Science and Engineering},
	volume = {15},
	year = {2018},
	month = {Jan-04-2018},
	pages = {852 - 862},
	issn = {1545-5955},
	doi = {10.1109/TASE.2017.2767379},
	url = {https://ieeexplore.ieee.org/document/8125731/http://xplorestaging.ieee.org/ielx7/8856/8332019/08125731.pdf?arnumber=8125731},
	author = {Kamra, Nitin and Kumar, T. K. Satish and Ayanian, Nora}
}
@proceedings {430,
	title = {Consensus Based Distributed Cooperative Control for Multiple Miniature Aerial Vehicles with Uncertainty},
	year = {2018},
	month = {11/2018},
	doi = {10.1109/SMC.2017.8122995},
	author = {Shafiqul Islam},
	editor = {Peter Liu and A. El Saddik}
}
@proceedings {429,
	title = {Consensus Based Distributed Robust Adaptive Control for Second-Order Nonlinear Multi-agent Systems with Uncertainty},
	year = {2018},
	month = {11/2018},
	doi = {10.1109/SMC.2018.00451},
	author = {Shafiqul Islam},
	editor = {Toufik Khawl and Abdelaziz Saeed Mohamed Alzaabi and Anderson Sunda-Meya}
}
@conference {334,
	title = {Collaborative Sampling Using Heterogeneous Marine Robots Driven by Visual Cues},
	booktitle = {Proceedings of the Conference on Computer and Robot Vision (CRV)},
	year = {2017},
	abstract = {This paper addresses distributed data sampling in marine environments using robotic devices. We present a method to strategically sample locally observable features using two classes of sensor platforms. Our system consists of a sophisticated autonomous surface vehicle (ASV) which strategically samples based on information provided by a team of inexpensive sensor nodes. The sensor nodes effectively extend the observational capabilities of the vehicle by capturing georeferenced samples from disparate and moving points across the region. The ASV uses this information, along with its own observations, to plan a path so as to sample points which it expects to be particularly informative. We compare our approach to a traditional exhaustive survey approach and show that we are able to effectively represent a region with less energy expenditure. We validate our approach through simulations and test the system on real robots in field.},
	doi = {10.1109/CRV.2017.49},
	author = {Sandeep Manjanna and Johanna Hansen and Quattrini~Li, Alberto and Ioannis Rekleitis and Gregory Dudek}
}
@proceedings {431,
	title = {Consensus Based Distributed Cooperative Control for Multiple Miniature Aerial Vehicles with Uncertainty},
	year = {2017},
	month = {11/2017},
	publisher = {IEEE},
	doi = {10.1109/SMC.2017.8122995},
	author = {Shafiqul Islam},
	editor = {P. X. Liu and A. El Saddik}
}
@conference {357,
	title = {Crazyswarm: A large nano-quadcopter swarm},
	booktitle = {2017 IEEE International Conference on Robotics and Automation (ICRA)2017 IEEE International Conference on Robotics and Automation (ICRA)},
	year = {2017},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Singapore, Singapore},
	doi = {10.1109/ICRA.2017.7989376},
	url = {http://ieeexplore.ieee.org/document/7989376/http://xplorestaging.ieee.org/ielx7/7960754/7988677/07989376.pdf?arnumber=7989376},
	author = {Preiss, James A. and Honig, Wolfgang and Sukhatme, Gaurav S. and Ayanian, Nora}
}
@article {210,
	title = {Cooperative Multi-Robot Patrol with Bayesian Learning},
	journal = {Autonomous Robots},
	year = {2016},
	author = {Portugal, D. and Rocha, R. P.}
}
@article {189,
	title = {Cooperative Control for Target Tracking with Onboard Sensing},
	journal = {International Journal of Robotics Research},
	volume = {34},
	year = {2015},
	month = {November},
	pages = {1660-1677},
	author = {Karol Hausman and Joerg Mueller and Abishek Hariharan and Nora Ayanian and Gaurav Sukhatme}
}
@conference {AyanianControlling2014,
	title = {Controlling a Team of Robots from a Single Input},
	booktitle = {IEEE Int{\textquoteright}l Conf. Robotics and Automation},
	year = {2014},
	month = {Jun},
	pages = {1755 - 1762},
	address = {Hong Kong},
	author = {Nora Ayanian and Andrew Spielberg and Matthew Arbesfeld and Jason Strauss and Daniela Rus}
}
@conference {HausmanCooperative2014,
	title = {Cooperative Control for Target Tracking with Onboard Sensing},
	booktitle = {International Symposium of Robotics Research},
	year = {2014},
	month = {Jun},
	address = {Morocco},
	author = {Karol Hausman and Joerg Mueller and Abishek Hariharan and Nora Ayanian and Gaurav Sukhatme}
}
@conference {37,
	title = {Coverage search in 3D},
	booktitle = {Proc. of the {IEEE} Int. Workshop on Safety, Security and Rescue Robotics {(SSRR)},
	year = {2013},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Linkoeping, Sweden},
	abstract = {Searching with a sensor for objects and to observe parts of a known environment efficiently is a fundamental problem in many real-world robotic applications such as household robots searching for objects, inspection robots searching for leaking pipelines, and rescue robots searching for survivors after a disaster. We consider the problem of identifying and planning efficient view point sequences for covering complex 3d environments. We compare empirically several variants of our algorithm that allow to trade-off schedule computation against execution time. Our results demonstrate that, despite the intractability of the overall problem, computing effective solutions for coverage search in real 3d environments is feasible.},
	keywords = {3D environments, coverage search, Educational institutions, execution time, household robots, image sequences, inspection robots, leaking pipelines search, objects search, path planning, Planning, rescue robots, Robot sensing systems, robot vision, robotic applications, schedule computation, Search problems, sensor, service robots, solid modelling, survivors search, Three-dimensional displays, Traveling salesman problems, view point sequences},
	doi = {10.1109/SSRR.2013.6719340},
	author = {Dornhege, C. and Kleiner, A. and Kolling, A.}
}
@conference {36,
	title = {Coverage search in 3D},
	year = {2013},
	address = {Linkoeping, Sweden},
	abstract = {Searching with a sensor for objects and to observe parts of a known environment efficiently is a fundamental problem in many real-world robotic applications such as household robots searching for objects, inspection robots searching for leaking pipelines, and rescue robots searching for survivors after a disaster. We consider the problem of identifying and planning efficient view point sequences for covering complex 3d environments. We compare empirically several variants of our algorithm that allow to trade-off schedule computation against execution time. Our results demonstrate that, despite the intractability of the overall problem, computing effective solutions for coverage search in real 3d environments is feasible.},
	keywords = {3D environments, coverage search, Educational institutions, execution time, household robots, image sequences, inspection robots, leaking pipelines search, objects search, path planning, Planning, rescue robots, Robot sensing systems, robot vision, robotic applications, schedule computation, Search problems, sensor, service robots, solid modelling, survivors search, Three-dimensional displays, Traveling salesman problems, view point sequences},
	doi = {10.1109/SSRR.2013.6719340},
	author = {Dornhege, C. and Kleiner, A. and Kolling, A.}
}
@article {134,
	title = {On Cooperative Patrolling: Optimal Trajectories, Complexity Analysis, and Approximation Algorithms},
	journal = {IEEE Transaction on Robotics},
	volume = {28},
	year = {2012},
	month = {06/2012},
	pages = {592-606},
	abstract = {The subject of this work is the patrolling of an environment with the aid of a team of autonomous agents. We consider both the design of open-loop trajectories with optimal properties, and of distributed control laws converging to optimal trajectories. As performance criteria, the refresh time and the latency are considered, i.e., respectively, time gap between any two visits of the same region, and the time necessary to inform every agent about an event occurred in the environment. We associate a graph with the environment, and we study separately the case of a chain, tree, and cyclic graph. For the case of chain graph, we first describe a minimum refresh time and latency team trajectory, and we propose a polynomial time algorithm for its computation. Then, we describe a distributed procedure that steers the robots toward an optimal trajectory. For the case of tree graph, a polynomial time algorithm is developed for the minimum refresh time problem, under the technical assumption of a constant number of robots involved in the patrolling task. Finally, we show that the design of a minimum refresh time trajectory for a cyclic graph is NP-hard, and we develop a constant factor approximation algorithm.},
	keywords = {Coverage, Distributed algorithms, Multi-robot systems, Patrolling / Surveillance},
	url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6122514},
	author = {Fabio Pasqualetti and Antonio Franchi and Francesco Bullo}
}
@inbook {217,
	title = {Computational Science and Its Applications - ICCSA 2011: International Conference, Santander, Spain, June 20-23, 2011. Proceedings, Part III},
	year = {2011},
	pages = {58{\textendash}73},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	chapter = {Multi-robot Visual Coverage Path Planning: Geometrical Metamorphosis of the Workspace through Raster Graphics Based Approaches},
	address = {Berlin, Heidelberg},
	isbn = {978-3-642-21931-3},
	doi = {10.1007/978-3-642-21931-3_5},
	url = {http://dx.doi.org/10.1007/978-3-642-21931-3_5},
	author = {Valente, Jo{\~a}o and Barrientos, Antonio and Del Cerro, Jaime and Rossi, Claudio and Colorado, Julian and Sanz, David and Garz{\'o}n, Mario},
	editor = {Murgante, Beniamino and Gervasi, Osvaldo and Iglesias, Andr{\'e}s and Taniar, David and Apduhan, Bernady O.}
}
@mastersthesis {AyanianThesis,
	title = {Coordination of Multirobot Teams and Groups in Constrained Environments: Models, Abstractions, and Control Policies},
	year = {2011},
	school = {University of Pennsylvania},
	type = {phd},
	author = {Nora Ayanian}
}
@book {153,
	title = {Cells and Robots: Modeling and Control of Large-Size Agent Populations},
	series = {Springer Tracts in Advanced Robotics},
	volume = {32},
	year = {2007},
	publisher = {Springer},
	organization = {Springer},
	author = {Dejan Milutinovi{\'c} and Pedro Lima}
}
@article {209,
	title = {Cooperative Multi-Robot Systems: a study of Vision-based 3-D Mapping using Information Theory},
	journal = {Robotics and Autonomous Systems},
	volume = {53},
	year = {2005},
	month = {Dec.},
	pages = {282-311},
	author = {Rocha, R. and Dias, J. and Carvalho, A.}
}
