@article {412,
	title = {Exploration and Mapping with Groups of Robots: Recent Trends},
	journal = {Current Robotics Reports},
	year = {2020},
	month = {Sep-09-2020},
	abstract = {Purpose of Review
Multi-robot exploration{\textemdash}i.e., the problem of mapping unknown features of an environment{\textemdash}is fundamental in many tasks, including search and rescue, planetary exploration, and environmental monitoring. This article surveys recent literature with the aim at identifying current research trends, open challenges, and future directions.

Recent Findings
Since the first formalization of the exploration problem, current research has extended systems and algorithms to map 3D environments and more complex phenomena and considered real-world constraints. Deep learning-based approaches have seen some preliminary applications in decision-making.

Summary
While current research has been progressing towards systems that can work in the real world, long-term exploration in large unstructured environments with complex phenomena to map is still an open problem. This introduces opportunities for exciting research, including but not limited to generalized frameworks that bridge the gap between theory and practice, learning-based approaches, and robustness to failure and attacks, so that robots can be deployed safely in real-world environments.},
	keywords = {Exploration, Mapping, Multi-robot systems},
	doi = {10.1007/s43154-020-00030-5},
	url = {http://link.springer.com/10.1007/s43154-020-00030-5},
	author = {Quattrini~Li, Alberto}
}
@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}
}
@conference {39,
	title = {Fast Guaranteed Search With Unmanned Aerial Vehicles},
	booktitle = {Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)},
	year = {2013},
	abstract = {In this paper we consider the problem of searching for an arbitrarily smart and fast evader in a large environment with a team of unmanned aerial vehicles (UAVs) while providing guarantees of detection. Our emphasis is on the fast execution of efficient search strategies that minimize the number of UAVs and the search time. We present the first approach for computing fast search strategies utilizing additional searchers to speed up the execution time and thereby enabling large scale UAV search. In order to scale to very large environments when using UAVs one would either have to overcome the energy limitations of UAVs or pay the cost of utilizing additional UAVs to speed up the search. Our approach is based on coordinating UAVs on sweep lines, covered by the UAV sensors, that move simultaneously through an environment. We present some simulation results that show a significant reduction in execution time when using multiple UAVs and a demonstration of a real system with three ARDrones.},
	keywords = {AR.Drone 2.0, autonomous aerial vehicles, Delays, fast guaranteed search, Multi-robot systems, Robot kinematics, Robot sensing systems, search problem, Search problems, search strategies, sensors, Surveillance, UAV sensors, unmanned aerial vehicles},
	doi = {10.1109/IROS.2013.6697229},
	author = {Kolling, A. and Kleiner, A. and Rudol, P.}
}
@conference {38,
	title = {Fast task-sequence allocation for heterogeneous robot teams with a human in the loop},
	booktitle = {Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems {(IROS)},
	year = {2013},
	abstract = {Efficient task allocation with timing constraints to a team of possibly heterogeneous robots is a challenging problem with application, e.g., in search and rescue. In this paper a mixed-integer linear programming (MILP) approach is proposed for assigning heterogeneous robot teams to the simultaneous completion of sequences of tasks with specific requirements such as completion deadlines. For this purpose our approach efficiently combines the strength of state of the art Mixed Integer Linear Programming (MILP) solvers with human expertise in mission scheduling. We experimentally show that simple and intuitive inputs by a human user have substantial impact on both computation time and quality of the solution. The presented approach can in principle be applied to quite general missions for robot teams with human supervision.},
	keywords = {computation time, Computational modeling, fast task sequence allocation, heterogeneous robot teams, heterogeneous robots, human in the loop, human supervision, human user, integer programming, linear programming, Mathematical model, MILP solvers, mission scheduling, mixed integer linear programming, Multi-robot systems, Resource management, Robot kinematics, Schedules, task allocation},
	doi = {10.1109/IROS.2013.6696570},
	author = {Petersen, K. and Kleiner, A. and Von Stryk, O.}
}
@conference {44,
	title = {Guaranteed search with large teams of unmanned aerial vehicles},
	booktitle = {Proc. of the {IEEE} Int. Conf. on Robotics and Automation (ICRA)},
	year = {2013},
	address = {Karlsruhe, Germany},
	abstract = {We consider the problem of detecting moving and evading targets by a team of coordinated unmanned aerial vehicles (UAVs) in large and complex 2D and 2.5D environments. Our approach is based on the coordination of 2D sweep lines that move through the environment to clear it from all contamination, representing the possibility of a target being located in an area, and thereby detecting all targets. The trajectories of the UAVs are implicitly given by the motion of these sweep lines and their costs are determined by the number of UAVs needed. A novel algorithm that computes low cost coordination strategies of the UAV sweep lines in simply connected polygonal environments is presented. The resulting strategies are then converted to strategies clearing multiply connected and 2.5D environments. Experiments on real and artificial elevation maps with complex visibility constraints are presented and demonstrate the feasibility and scalability of the approach. The algorithms used for the experiments are made available on a public repository.},
	keywords = {2D environment, 2D sweep lines, autonomous aerial vehicles, collision avoidance, Contamination, coordinated unmanned aerial vehicle team, guaranteed search, helicopters, low cost coordination strategies, Multi-robot systems, multiply-connected 2.5D environment, public repository, quadrotors, robot operating system, Robot sensing systems, ROS framework, Search problems, Shape, simply-connected polygonal environment, sweep line motion, Trajectory, trajectory computing, trajectory control, UAV trajectory, unmanned aerial vehicles},
	doi = {10.1109/ICRA.2013.6630990},
	author = {Kleiner, A. and Kolling, A.}
}
@conference {146,
	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},
	author = {Marco Cognetti and Paolo Stegagno and Antonio Franchi and Giuseppe Oriolo and Heinrich H. B{\"u}lthoff}
}
@article {141,
	title = {Bilateral Teleoperation of Groups of Mobile Robots with Time-Varying Topology},
	journal = {IEEE Transaction on Robotics},
	volume = {28},
	year = {2012},
	month = {10/2012},
	pages = {1019	-1033},
	abstract = {In this paper, a novel decentralized control strategy for bilaterally teleoperating heterogeneous groups of mobile robots from different domains (aerial, ground, marine and under- water) is proposed. By using a decentralized control architecture, the group of robots, treated as the slave-side, is made able to navigate in a cluttered environment while avoiding obstacles, inter-robot collisions and following the human motion commands. Simultaneously, the human operator acting on the master side is provided with a suitable force feedback informative of the group response and of the interaction with the surrounding environment. Using passivity based techniques, we allow the behavior of the group to be as flexible as possible with arbitrary split and join events (e.g., due to inter-robot visibility/packet losses or specific task requirements) while guaranteeing the stability of the system. We provide a rigorous analysis of the system stability and steady-state characteristics, and validate performance through human/hardware-in-the-tloop simulations by considering a heterogeneous fleet of UAVs and UGVs as case study. Finally, we also provide an experimental validation with 4 quadrotor UAV},
	keywords = {Bilateral Shared Control of Mobile Robots, Decentralized control, Distributed algorithms, Force feedback, Haptics, Motion control of multiple robots, Multi-robot systems, Teleoperation},
	author = {Antonio Franchi and Cristian Secchi and Hyoung Il Son and Heinrich H. B{\"u}lthoff and Paolo Robuffo Giordano}
}
@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}
}
@article {135,
	title = {Distributed Pursuit-Evasion without Mapping and Global Localization via Local Frontiers},
	journal = {Autonomous Robots},
	volume = {32},
	year = {2012},
	month = {01/2012},
	pages = {81-95},
	abstract = {This paper addresses a visibility-based pursuit-evasion problem in which a team of mobile robots with limited sensing and communication capabilities must coordinate to detect any evaders in an unknown, multiply-connected planar environment. Our distributed algorithm to guarantee evader detection is built around maintaining complete coverage of the frontier between cleared and contaminated regions while expanding the cleared region. We detail a novel distributed method for storing and updating this frontier without building a map of the environment or requiring global localization. We demonstrate the functionality of the algorithm through simulations in realistic environments and through hardware experiments. We also compare Monte Carlo results for our algorithm to the theoretical optimum area cleared as a function of the number of robots available.},
	keywords = {Coverage, Distributed algorithms, Multi-robot systems, Pursuit-evasion / Clearing},
	url = {http://www.springerlink.com/content/a02pr41790ll754w/},
	author = {Joseph W. Durham and Antonio Franchi and Francesco Bullo}
}
@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 {98,
	title = {Rigidity Maintenance Control for Multi-Robot Systems},
	booktitle = {2012 Robotics: Science and Systems Conference},
	year = {2012},
	month = {07/2012},
	address = {Sydney, Australia},
	abstract = {Rigidity of formations in multi-robot systems is important for formation control, localization, and sensor fusion. This work proposes a rigidity maintenance gradient controller for a multi-agent robot team. To develop such a controller, we first provide an alternative characterization of the rigidity matrix and use that to introduce the novel concept of the rigidity eigenvalue. We provide a necessary and sufficient condition relating the positivity of the rigidity eigenvalue to the rigidity of the formation. The rigidity maintenance controller is based on the gradient of the rigidity eigenvalue with respect to each robot position. This gradient has a naturally distributed structure, and is thus amenable to a distributed implementation. Additional requirements such as obstacle and inter-agent collision avoidance, as well as typical constraints such as limited sensing/communication ranges and line-of-sight occlusions, are also explicitly considered. Finally, we present a simulation with a group of seven quadrotor UAVs to demonstrate and validate the theoretical results.},
	keywords = {Decentralized control, Formation control, Motion control of multiple robots, Multi-robot systems, Rigidity mainenance},
	author = {Daniel Zelazo and Antonio Franchi and Frank Allg{\"o}wer and Heinrich H. B{\"u}lthoff and Paolo Robuffo Giordano}
}
@article {139,
	title = {Shared Control: Balancing Autonomy and Human Assistance with a Group of Quadrotor UAVs.},
	journal = {IEEE Robotics and Automation Magazine, Special Issue on Aerial Robotics and the Quadrotor Platform},
	volume = {19},
	year = {2012},
	month = {09/2012},
	pages = {57-68},
	abstract = {In this paper, we present a complete control framework and associated experimental testbed for the bilateral shared control of a group of quadrotor UAVs. This control architecture is applicable to any task and allows to integrate: i) a decentralized topological motion control (responsible for the mutual interactions in the UAV formation), ii) a human assistance module (allowing human intervention, whenever needed, on some aspects of the UAV group behavior), and iii) a force-feedback possibility (increasing the telepresence of the human assistants by providing suitable haptic cues informative of the UAV behavior). We will show, as worked-out case studies, how to specialize the topological motion controller to the relevant cases of constant, unconstrained and connected group topologies, and how to let a human operator intervening at the level of single UAVs or of the whole group dynamics. A detailed description of the experimental testbed is also provided with emphasis on the quadrotor UAV hardware and software architectures. Finally, the versatility of the proposed framework is demonstrated by means of experiments with real UAVs. Although quadrotors are used as actual robotic platforms, the proposed framework can be straightforwardly extended to many different kinds of UAVs with similar motion characteristics.},
	keywords = {Bilateral Shared Control of Mobile Robots, Decentralized control, Force feedback, Formation control, Haptics, Middleware for robotics, Motion control of multiple robots, Multi-robot systems, UAV hardware platforms},
	author = {Antonio Franchi and Cristian Secchi 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}
}
@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 {140,
	title = {The Sensor-based Random Graph Method for Cooperative Robot Exploration},
	journal = {IEEE/ASME Transaction on Mechatronics},
	volume = {14},
	year = {2009},
	month = {04/2009},
	pages = {163-175},
	abstract = {We present a decentralized cooperative exploration strategy for a team of mobile robots equipped with range finders. A roadmap of the explored area, with the associate safe region, is built in the form of a Sensor-based Random Graph (SRG). This is expanded by the robots by using a randomized local planner which automatically realizes a trade-off between information gain and navigation cost. The nodes of the SRG represent view configurations that have been visited by at least one robot, and are connected by arcs that represent safe paths. These paths have been actually traveled by the robots or added to the SRG to improve its connectivity. Decentralized cooperation and coordination mechanisms are used so as to guarantee exploration efficiency and avoid conflicts. Simulations and experiments are presented to show the performance of the proposed technique.},
	keywords = {Coverage, Distributed algorithms, Exploration, Multi-robot systems},
	author = {Antonio Franchi and Luigi Freda and Giuseppe Oriolo and Marilena Vendittelli}
}
@article {181,
	title = {Naval Mine Countermeasure Missions},
	journal = {Robotics Automation Magazine, IEEE},
	volume = {15},
	year = {2008},
	pages = {45-52},
	keywords = {Analytical models, autonomous underwater vehicles, AUV, communication windows, Delay, DEMiR-CF framework, distributed incremental multirobot task selection scheme, Land vehicles, mobile robots, Multi-robot systems, multirobot-cooperation framework, naval engineering, naval mine countermeasure missions, online dynamic task allocation system, Performance analysis, remotely operated vehicles, scheduling, Sea floor, Sonar detection, task execution, task scheduling, undersea operations, Underwater communication, underwater vehicles, unmanned aerial vehicles},
	issn = {1070-9932},
	doi = {10.1109/M-RA.2007.914920},
	author = {Sanem Sariel and Tucker Balch and Nadia Erdogan}
}
@conference {HKG:NA:CASE08,
	title = {Recycling controllers},
	booktitle = {IEEE International Conf. on Automation Science and Engineering},
	year = {2008},
	month = {Aug},
	pages = {772-777},
	address = {Washington, DC},
	keywords = {atomic controller, automata theory, collision avoidance, control scheme design, control system synthesis, deadlock reduction, discrete automaton, heterogeneous robot team, mobile robots, Multi-robot systems, recycling controller},
	doi = {10.1109/COASE.2008.4626521},
	author = {Hadas Kress-Gazit and Nora Ayanian and George J. Pappas and Vijay Kumar}
}
@conference {184,
	title = {Incremental multi-robot task selection for resource constrained and interrelated tasks},
	booktitle = {Proceedings of The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
	year = {2007},
	keywords = {coordinated task selection problem, Intelligent robots, interrelated tasks, Multi-robot systems, multi-robot task selection, Notice of Violation, Performance evaluation, resource constrained tasks, Resource management, Robot kinematics, Robot sensing systems, Robotics and automation, Runtime, scheduling, USA Councils},
	doi = {10.1109/IROS.2007.4399519},
	author = {Sanem Sariel and Tucker Balch and Nadia Erdogan}
}
