@article {kurrasensing,
	title = {Sensing and Evaluation of Bird Comfort Using Internet of Things and Machine Learning},
	year = {Submitted},
	author = {Kurra, Naveen}
}
@article {bathulasynthetic,
	title = {Synthetic Instincts: Echoing Reinforcement Learning Agents for Behavior Tree Generation},
	year = {Submitted},
	author = {Bathula, Shailendra Sekhar Reddy}
}
@article {ghanta2024space,
	title = {SPACE: 3D Spatial Co-operation and Exploration Framework for Robust Mapping and Coverage with Multi-Robot Systems},
	journal = {arXiv preprint arXiv:2411.02524},
	year = {2024},
	author = {Ghanta, Sai Krishna and Parasuraman, Ramviyas}
}
@conference {latif2023seal,
	title = {SEAL: Simultaneous Exploration and Localization in Multi-Robot Systems},
	booktitle = {2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
	number = {Forthcoming},
	year = {2023},
	author = {Latif, Ehsan and Parasuraman, Ramviyas}
}
@article {yang2023strategy,
	title = {A strategy-oriented bayesian soft actor-critic model},
	journal = {Procedia Computer Science},
	volume = {220},
	year = {2023},
	pages = {561{\textendash}566},
	publisher = {Elsevier},
	author = {Yang, Qin and Parasuraman, Ramviyas}
}
@conference {sanjay2023systems,
	title = {Systems Design Concepts Mimicking Bio-inspired Self-Assembly},
	booktitle = {9th International Conference on Research Into Design (ICoRD) 2023},
	year = {2023},
	author = {Sanjay Sarma, OV and Ardoin, Cameron and Ibrahim, Israr M and Parasuraman, Ramviyas and Pidaparti, Ramana M}
}
@mastersthesis {yang2022self,
	title = {Self-Adaptive Swarm System},
	year = {2022},
	school = {University of Georgia},
	type = {phd},
	author = {Yang, Qin}
}
@article {471,
	title = {Self-Stabilizing Self-Assembly},
	journal = {IEEE Robotics and Automation Letters},
	volume = {7},
	year = {2022},
	pages = {9763-9769},
	doi = {10.1109/LRA.2022.3191795},
	author = {J{\'\i}lek, Martin and Str{\'a}nsk{\'a}, Kate{\v r}ina and Somr, Michael and Kulich, Miroslav and Zeman, Jan and P{\v r}eu{\v c}il, Libor}
}
@mastersthesis {ravipati2022semantic,
	title = {Semantic Material Labeling of 3D Point Clouds using RGBD Data and Visual SLAM},
	year = {2022},
	school = {University of Georgia},
	type = {phd},
	author = {Ravipati, Siva Krishna}
}
@conference {munir2022sharing,
	title = {Sharing Autonomy of Exploration and Exploitation via Control Interface},
	booktitle = {ICRA 2022 Workshop on Shared Autonomy in Physical Human-Robot Interaction: Adaptability and Trust},
	year = {2022},
	author = {Munir, Aiman and Parasuraman, Ramviyas}
}
@conference {Zhao2022,
	title = {SnailBot: A Continuously Dockable Modular Self-reconfigurable Robot Using Rocker-bogie Suspension},
	booktitle = {2022 International Conference on Robotics and Automation (ICRA)},
	year = {2022},
	pages = {4261{\textendash}4267},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Philadelphia, PA, USA},
	abstract = {This paper proposes a novel modular self-assembling, self-reconfiguring robot with the 3D continuous dock called {\textquotedblleft}SnailBot{\textquotedblright}. SnailBot mainly consists of a spherical ferromagnetic shell and a six-wheel rocker chassis with embedded magnets. Unlike many other existing modular self-reconfigurable robots with fixed docking locations, SnailBot uses the 3D continuous dock to attach to its peers regardless of alignment. This freeform docking mechanism can greatly improve the efficiency of self-reconfiguration and reduce docking failures because there is nearly no constraint in the location of the connector. Compared with the existing freeform MSRR, SnailBot can form a more structurally stable connection to its peers without loss of connection efficiency. Owing to the excellent obstacle crossing ability of the rocker-bogie suspension, the robot can freely crawl on other modules in the form of a sliding sphere. Experiments demonstrate the basic actions of a single module and some applications of SnailBots, such as a manipulator.},
	keywords = {Automation, Connectors, Manipulators, Three-dimensional displays},
	isbn = {978-1-7281-9682-4},
	doi = {10.1109/ICRA46639.2022.9811779},
	author = {Da Zhao and Tin Lun Lam}
}
@conference {venkata2022study,
	title = {A study on the ephemeral nature of knowledge shared within multiagent systems},
	booktitle = {5th International Symposium on Swarm Behavior and Bio-Inspired Robotics (SWARM)},
	year = {2022},
	author = {Venkata, Sanjay Sarma Oruganti and Parasuraman, Ramviyas and Pidaparti, Ramana}
}
@article {yang2021self,
	title = {Self-Adaptive Swarm System (SASS)},
	journal = {arXiv preprint arXiv:2106.04679},
	year = {2021},
	author = {Yang, Qin}
}
@article {Guo2021,
	title = {Semantic Histogram Based Graph Matching for Real-Time Multi-Robot Global Localization in Large Scale Environment},
	journal = {IEEE Robotics and Automation Letters},
	volume = {6},
	year = {2021},
	pages = {8349{\textendash}8356},
	publisher = {IEEE},
	abstract = {The core problem of visual multi-robot simultaneous localization and mapping (MR-SLAM) is how to efficiently and accurately perform multi-robot global localization (MR-GL). The difficulties are two-fold. The first is the difficulty of global localization for significant viewpoint difference. Appearance-based localization methods tend to fail under large viewpoint changes. Recently, semantic graphs have been utilized to overcome the viewpoint variation problem. However, the methods are highly time-consuming, especially in large-scale environments. This leads to the second difficulty, which is how to perform real-time global localization. In this letter, we propose a semantic histogram based graph matching method that is robust to viewpoint variation and can achieve real-time global localization. Based on that, we develop a system that can accurately and efficiently perform MR-GL for both homogeneous and heterogeneous robots. The experimental results show that our approach is about 30 times faster than Random Walk based semantic descriptors. Moreover, it achieves an accuracy of 95\% for global localization, while the accuracy of the state-of-the-art method is 85\%.},
	keywords = {Global localization, Histograms, large viewpoint difference, Location awareness, multi-robot map merging, Real-time systems, semantic SLAM, Semantics, Simultaneous localization and mapping, Three-dimensional displays, Visualization},
	issn = {2377-3774},
	doi = {10.1109/LRA.2021.3058935},
	author = {Xiyue Guo and Junjie Hu and Junfeng Chen and Fuqin Deng and Tin Lun Lam}
}
@article {Hunt2020a,
	title = {SPIDER: a Bioinspired Swarm Algorithm for Adaptive Risk-Taking},
	journal = {Artificial Life Conference Proceedings},
	volume = {32},
	year = {2020},
	note = {doi: 10.1162/isal_a_00279},
	month = {7},
	pages = {44-51},
	publisher = {MIT Press},
	abstract = {Robot swarms can solve tasks that are impossible or too hazardous for single robots. For example, following a nuclear radiation leak, a user may wish to establish a distributed communication chain that partly extends into the most dangerous areas to gather new information. The challenge is to create long chains while maintaining chain connectivity (?connected reach?), where those at the distant end of the chain are more likely to be disconnected. Here we take the concept of dynamic ?boldness? levels from animal behavior (Stegodyphus social spiders) to explore such risky environments in a way that adapts to the size of the group. Boldness is implemented as a continuous variable associated with the risk appetite of individuals to explore regions more distant from a central base. We present a decentralized mechanism for robots, based on the frequency of their social interactions, to adaptively take on ?bold? and ?shy? behaviors. Using this new bioinspired algorithm, which we call SPIDER, swarms are shown to adapt rapidly to the loss of bold individuals by regenerating a suitable shy?bold distribution, with fewer bolder individuals in smaller groups. This allows them to dynamically trade-off the benefits and costs of long chains (information retrieval versus loss of robots) and demonstrates the particular advantage of this approach in hazardous or adversarial environments.},
	doi = {10.1162/isal_a_00279},
	url = {https://www.mitpressjournals.org/doi/abs/10.1162/isal_a_00279},
	author = {Edmund R Hunt and George Jenkinson and Michael Wilsher and Carl P Dettmann and Sabine Hauert}
}
@conference {yang2019self,
	title = {Self-reactive planning of multi-robots with dynamic task assignments},
	booktitle = {2019 International Symposium on Multi-Robot and Multi-Agent Systems (MRS)},
	year = {2019},
	pages = {89{\textendash}91},
	publisher = {IEEE},
	organization = {IEEE},
	author = {Yang, Qin and Luo, Zhiwei and Song, Wenzhan and Parasuraman, Ramviyas}
}
@article {kim2019soft,
	title = {Soft-packaged sensory glove system for human-like natural interaction and control of prosthetic hands},
	journal = {NPG Asia Materials},
	volume = {11},
	number = {1},
	year = {2019},
	pages = {43},
	publisher = {Nature Publishing Group UK London},
	author = {Kim, Min Ku and Parasuraman, Ramviyas Nattanmai and Wang, Liu and Park, Yeonsoo and Kim, Bongjoong and Lee, Seung Jun and Lu, Nanshu and Min, Byung-Cheol and Lee, Chi Hwan}
}
@conference {418,
	title = {A Search-Based Approach to Solve Pursuit-Evasion Games with Limited Visibility in Polygonal Environments},
	booktitle = {International Conference on Autonomous \& Multiagent Systems (AAMAS)},
	year = {2018},
	url = {http://dl.acm.org/citation.cfm?id=3237383.323795},
	author = {Quattrini Li, Alberto and Raffaele Fioratto and Francesco Amigoni and Volkan Isler}
}
@article {parasuraman2018special,
	title = {Special Issue on {\textquotedblleft}Assistive Robotics{\textquotedblright}},
	journal = {Technologies},
	volume = {6},
	number = {4},
	year = {2018},
	pages = {95},
	publisher = {MDPI AG},
	author = {Parasuraman, Ramviyas and Min, Byung-Cheol}
}
@article {331,
	title = {Strategies for coordinated multirobot exploration with recurrent connectivity constraints},
	journal = {Autonomous Robots},
	volume = {42},
	year = {2018},
	pages = {875{\textendash}894},
	abstract = {During several applications, such as search and rescue, robots must discover new information about the environment and, at the same time, share operational knowledge with a base station through an ad hoc network. In this paper, we design exploration strategies that allow robots to coordinate with teammates to form such a network in order to satisfy recurrent connectivity constraints{\textendash}-that is, data must be shared with the base station when making new observations at the assigned locations. Current approaches lack in flexibility due to the assumptions made about the communication model. Furthermore, they are sometimes inefficient because of the synchronous way they work: new plans are issued only once all robots have reached their goals. This paper introduces two novel asynchronous strategies that work with arbitrary communication models. In this paper, {\textquoteleft}asynchronous{\textquoteright} means that it is possible to issue new plans to subgroups of robots, when they are ready to receive them. First, we propose a single-stage strategy based on Integer Linear Programming for selecting and assigning robots to locations. Second, we design a two-stage strategy to improve computational efficiency, by separating the problem of locations{\textquoteright} selection from that of robot-location assignments. Extensive testing both in simulation and with real robots show that the proposed strategies provide good situation awareness at the base station while efficiently exploring the environment.},
	keywords = {Communication constraints, Exploration, Multirobot systems, Recurrent connectivity},
	doi = {10.1007/s10514-017-9652-y},
	author = {Jacopo Banfi and Quattrini~Li, Alberto and Ioannis Rekleitis and Francesco Amigoni and Nicola Basilico}
}
@conference {356,
	title = {Summary: Multi-Agent Path Finding with Kinematic Constraints},
	booktitle = {Twenty-Sixth International Joint Conference on Artificial IntelligenceProceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence},
	year = {2017},
	publisher = {International Joint Conferences on Artificial Intelligence Organization},
	organization = {International Joint Conferences on Artificial Intelligence Organization},
	address = {Melbourne, AustraliaCalifornia},
	doi = {10.24963/ijcai.201710.24963/ijcai.2017/684},
	url = {https://www.ijcai.org/proceedings/2017https://www.ijcai.org/proceedings/2017/684},
	author = {Honig, Wolfgang and Kumar, T. K. Satish and Cohen, Liron and Ma, Hang and Xu, Hong and Ayanian, Nora and Koenig, Sven}
}
@conference {366,
	title = {SAGL: A New Heuristic for Multi-Robot Routing with Complex Tasks},
	booktitle = {2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI)},
	year = {2016},
	publisher = {IEEE},
	organization = {IEEE},
	address = {San Jose, CA, USA},
	doi = {10.1109/ICTAI.2016.0087},
	url = {http://ieeexplore.ieee.org/document/7814647/http://xplorestaging.ieee.org/ielx7/7811909/7814561/07814647.pdf?arnumber=7814647},
	author = {Xu, Hong and Kumar, T.K. Satish and Johnke, Dylan and Ayanian, Nora and Koenig, Sven}
}
@conference {264,
	title = {Scalable value approximation for multiple target tail-chase with collision avoidance},
	booktitle = {2016 IEEE 55th Conference on Decision and Control (CDC)},
	year = {2016},
	month = {Dec},
	keywords = {Cost function, Dynamic programming, Games, Hazards, Markov processes, Mathematical model, Optimal control},
	doi = {10.1109/CDC.2016.7798645},
	author = {A. Hashemi and D. Milutinovi{\'c} and D. W. Casbeer}
}
@booklet {li2016spatial,
	title = {Spatial wireless connectivity prediction for mobile robots},
	year = {2016},
	author = {Li, Mengchan}
}
@article {167,
	title = {A semantically-informed multirobot system for exploration of relevant areas in search and rescue settings},
	journal = {Autonomous Robots},
	year = {2015},
	pages = {1{\textendash}17},
	abstract = {Coordinated multirobot exploration involves autonomous discovering and mapping of the features of initially unknown environments by using multiple robots. Autonomously exploring mobile robots are usually driven, both in selecting locations to visit and in assigning them to robots, by knowledge of the already explored portions of the environment, often represented in a metric map. In the literature, some works addressed the use of semantic knowledge in exploration, which, embedded in a semantic map, associates spatial concepts (like {\textquoteleft}rooms{\textquoteright} and {\textquoteleft}corridors{\textquoteright}) with metric entities, showing its effectiveness in improving the total area explored by robots. In this paper, we build on these results and propose a system that exploits semantic information to push robots to explore relevant areas of initially unknown environments, according to a priori information provided by human users. Discovery of relevant areas is significant in some search and rescue settings, in which human rescuers can instruct robots to search for victims in specific areas, for example in cubicles if a disaster happened in an office building during working hours. We propose to speed up the exploration of specific areas by using semantic information both to select locations to visit and to determine the number of robots to allocate to those locations. In this way, for example, more robots could be assigned to a candidate location in a corridor, so the attached rooms can be explored faster. We tested our semantic-based multirobot exploration system within a reliable robot simulator and we evaluated its performance in realistic search and rescue indoor settings with respect to state-of-the-art approaches.},
	keywords = {Coordinated multirobot exploration, Search and Rescue, Semantic map},
	issn = {1573-7527},
	doi = {10.1007/s10514-015-9480-x},
	url = {http://dx.doi.org/10.1007/s10514-015-9480-x},
	author = {Quattrini~Li, Alberto and Cipolleschi, Riccardo and Giusto, Michele and Amigoni, Francesco}
}
@article {147,
	title = {Self-Organized Aggregation without Computation},
	journal = {The International Journal of Robotics Research},
	volume = {33},
	year = {2014},
	pages = {1145-1161},
	keywords = {aggregation, minimal information processing, rendezvous, swarm robotics},
	doi = {10.1177/0278364914525244},
	author = {Gauci, Melvin and Chen, Jianing and Li, Wei and Dodd, Tony J. and Gross, Roderich}
}
@article {155,
	title = {Stochastic Optimal Enhancement of Distributed Formation Control Using Kalman Smoothers},
	journal = {Robotica},
	volume = {32},
	year = {2014},
	month = {03/2014},
	pages = {305-324},
	author = {Ross Anderson and Dejan Milutinovi{\'c}}
}
@conference {404,
	title = {On the security vulnerabilities of the virtual force approach to mobile sensor deployment},
	booktitle = {2013 Proceedings IEEE INFOCOM},
	year = {2013},
	author = {N. Bartolini and G. Bongiovanni and T. L. Porta and S. Silvestri}
}
@conference {336,
	title = {Semantically-Informed Coordinated Multirobot Exploration of Relevant Areas in Search and Rescue Settings},
	booktitle = {Proceedings of the 6th European Conference on Mobile Robots (ECMR)},
	year = {2013},
	abstract = {Coordinated multirobot exploration involves autonomous discovering of unknown features in environments by using multiple robots. Autonomously exploring mobile robots are driven by knowledge of the already explored portions of the environment, usually represented in a metric map. In the literature, some works addressed the use of semantic knowledge in exploration, which, embedded in a semantic map, associates spatial concepts (like {\textquoteleft}rooms{\textquoteright} and {\textquoteleft}corridors{\textquoteright}) with metric entities, showing its effectiveness to improve total explored area. In this paper, we build on these results and propose a system that exploits semantic information to push robots to explore areas that are relevant, according to a priori information provided by human users. We tested our semantic-based multirobot exploration system in a reliable robot simulator and evaluated its performance in realistic search and rescue settings with respect to state-of-the-art approaches.},
	doi = {10.1109/ECMR.2013.6698845},
	author = {Riccardo Cipolleschi and Michele Giusto and Quattrini~Li, Alberto and Francesco Amigoni}
}
@article {138,
	title = {Semi-Autonomous Haptic Teleoperation Control Architecture of Multiple Unmanned Aerial Vehicles},
	journal = {IEEE/ASME Transaction on Mechatronics, Focused Section on Aerospace Mechatronics},
	volume = {18},
	year = {2013},
	month = {08/2013},
	pages = {1334-1345},
	abstract = {We propose a novel semi-autonomous haptic teleoperation control architecture for multiple unmanned aerial vehicles (UAVs), consisting of three control layers: 1) UAV control layer, where each UAV is abstracted by, and is controlled to follow the trajectory of, its own kinematic Cartesian virtual point (VP); 2) VP control layer, which modulates each VP{\textquoteright}s motion according to the teleoperation commands and local artificial potentials (for VP-VP/VP-obstacle collision avoidance and VP-VP connectivity preservation); and 3) teleoperation layer, through which a single remote human user can command all (or some) of the VPs{\textquoteright} velocity while haptically perceiving the state of all (or some) of the UAVs and obstacles. Master-passivity/slave-stability and some asymptotic performance measures are proved. Experimental results using four custom-built quadrotor-type UAVs are also presented to illustrate the theory.},
	keywords = {Bilateral Shared Control of Mobile Robots, Motion control of multiple robots, UAV hardware platforms},
	author = {Dongjun Lee and Antonio Franchi and Hyoung Il Son and Heinrich H. B{\"u}lthoff and Paolo Robuffo Giordano}
}
@conference {parasuraman2013spatial,
	title = {Spatial sampling methods for improved communication for wireless relay robots},
	booktitle = {2013 International Conference on Connected Vehicles and Expo (ICCVE)},
	year = {2013},
	pages = {874{\textendash}880},
	publisher = {IEEE},
	organization = {IEEE},
	author = {Parasuraman, Ramviyas and Fabry, Thomas and Kershaw, Keith and Ferre, Manuel}
}
@article {107,
	title = {A Survey and Analysis of Multi-Robot Coordination},
	journal = {International Journal of Advanced Robotic Systems},
	volume = {10},
	year = {2013},
	month = {December},
	doi = {10.5772/57313},
	url = {http://www.intechopen.com/journals/international_journal_of_advanced_robotic_systems/a-survey-and-analysis-of-multi-robot-coordination},
	author = {Zhi Yan and Nicolas Jouandeau and Arab Ali Cherif}
}
@article {402,
	title = {Sensor Activation and Radius Adaptation (SARA) in Heterogeneous Sensor Networks},
	journal = {ACM Trans. Sen. Netw.},
	volume = {8},
	year = {2012},
	keywords = {Area coverage, heterogeneous devices, variable radii, wireless sensor networks},
	issn = {1550-4859},
	doi = {10.1145/2240092.2240098},
	url = {https://doi.org/10.1145/2240092.2240098},
	author = {N. Bartolini and Calamoneri, Tiziana and La Porta, Tom and Petrioli, Chiara and Silvestri, Simone}
}
@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 {46,
	title = {The SHERPA project: smart collaboration between humans and ground-aerial robots for improving rescuing activities in alpine environments},
	booktitle = {Proc. of the IEEE Int. Workshop on Safety, Security and Rescue Robotics (SSRR)},
	year = {2012},
	address = {College Station, US},
	abstract = {The goal of the paper is to present the foreseen research activity of the European project {\textquoteleft}{\textquoteleft}SHERPA{\textquoteright}{\textquoteright} whose activities will start officially on February 1th 2013. The goal of SHERPA is to develop a mixed ground and aerial robotic platform to support search and rescue activities in a real-world hostile environment, like the alpine scenario that is specifically targeted in the project. Looking into the technological platform and the alpine rescuing scenario, we plan to address a number of research topics about cognition and control. What makes the project potentially very rich from a scientific viewpoint is the heterogeneity and the capabilities to be owned by the different actors of the SHERPA system: the human rescuer is the {\textquoteleft}{\textquoteleft}busy genius{\textquoteright}{\textquoteright}, working in team with the ground vehicle, as the {\textquoteleft}{\textquoteleft}intelligent donkey{\textquoteright}{\textquoteright}, and with the aerial platforms, i.e. the {\textquoteleft}{\textquoteleft}trained wasps{\textquoteright}{\textquoteright} and {\textquoteleft}{\textquoteleft}patrolling hawks{\textquoteright}{\textquoteright}. Indeed, the research activity focuses on how the {\textquoteleft}{\textquoteleft}busy genius{\textquoteright}{\textquoteright} and the {\textquoteleft}{\textquoteleft}SHERPA animals{\textquoteright}{\textquoteright} interact and collaborate with each other, with their own features and capabilities, toward the achievement of a common goal.},
	keywords = {alpine environments, autonomous aerial vehicles, busy genius, Cognitive Systems, European project, Ground and Aerial Robotics, ground-aerial robots, human rescuer, intelligent donkey, patrolling hawks, real-world hostile environment, rescuing activities, Robust Control, Search and Rescue, search and rescue activities, SHERPA project, smart collaboration, telerobotics, trained wasps},
	doi = {10.1109/SSRR.2012.6523905},
	author = {Marconi, L. and Melchiorri, C. and Beetz, M. and Pangercic, D. and Siegwart, R. and Leutenegger, S. and Carloni, R. and Stramigioli, S. and Bruyninckx, H. and Doherty, P. and Kleiner, A. and Lippiello, V. and Finzi, A. and Siciliano, B. and Sala, A. and Tomatis, N.}
}
@conference {WagnerSubdimensional2012,
	title = {Subdimensional Expansion and Optimal Task Reassignment},
	booktitle = {AAAI Symposium on Combinatorial Search},
	year = {2012},
	month = {July},
	address = {Niagara Falls, ON, Canada},
	author = {Glenn Wagner and Howie Choset and Nora Ayanian}
}
@conference {nair2012swarm,
	title = {Swarm aggregation using artificial potential field and fuzzy sliding mode control with adaptive tuning technique},
	booktitle = {American Control Conference (ACC), 2012},
	year = {2012},
	pages = {6184{\textendash}6189},
	publisher = {IEEE},
	organization = {IEEE},
	author = {Nair, Ranjith Ravindranathan and Behera, Laxmidhar}
}
@conference {211,
	title = {A Survey on Multi-Robot Patrolling Algorithms},
	booktitle = {Proc. of 2nd Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS{\textquoteright}11)},
	year = {2011},
	month = {Feb.},
	address = {Costa da Caparica, Lisbon, Portugal},
	author = {Portugal, D. and Rocha, R.}
}
@inbook {NA:VK:DK:ISRR09,
	title = {Synthesis of Controllers to Create, Maintain, and Reconfigure Robot Formations with Communication Constraints},
	booktitle = {Robotics Research},
	series = {Springer Tracts in Advanced Robotics},
	volume = {70},
	year = {2011},
	pages = {625-642},
	publisher = {Springer Berlin / Heidelberg},
	organization = {Springer Berlin / Heidelberg},
	author = {Nora Ayanian and Kumar, Vijay and Koditschek, Daniel},
	editor = {Pradalier, C{\'e}dric and Siegwart, Roland and Hirzinger, Gerhard}
}
@conference {AyanianSynthesis2011,
	title = {Synthesis of Feedback Controllers for Multiple Aerial Robots with Geometric Constraints},
	booktitle = {Intl Conf Intelligent Robots and Systems},
	year = {2011},
	month = {Sept.},
	pages = {3126-3131},
	address = {San Francisco, CA},
	author = {Nora Ayanian and Vinutha Kallem and Vijay Kumar}
}
@conference {361,
	title = {Synthesis of feedback controllers for multiple aerial robots with geometric constraints},
	booktitle = {2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011)2011 IEEE/RSJ International Conference on Intelligent Robots and Systems},
	year = {2011},
	publisher = {IEEE},
	organization = {IEEE},
	address = {San Francisco, CA},
	isbn = {978-1-61284-454-1},
	doi = {10.1109/IROS.2011.6094943},
	url = {http://ieeexplore.ieee.org/document/6094943/http://xplorestaging.ieee.org/ielx5/6034548/6094399/06094943.pdf?arnumber=6094943},
	author = {Ayanian, Nora and Kallem, Vinutha and Kumar, Vijay}
}
@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}
}
@conference {NA:PW:AH:MR08,
	title = {Stochastic Control for Self-Assembly of {XB}ots},
	booktitle = {ASME Mechanisms and Robotics Conference},
	volume = {2},
	year = {2008},
	month = {August},
	pages = {1169-1176},
	address = {New York, NY},
	author = {Nora Ayanian and Paul White and Adam Hal{\'a}sz and Mark Yim and Vijay Kumar}
}
