@conference {Liang2022,
	title = {Energy Sharing Mechanism for a Freeform Robotic System - FreeBOT},
	booktitle = {2022 International Conference on Robotics and Automation (ICRA)},
	year = {2022},
	pages = {4232{\textendash}4238},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Philadelphia, PA, USA},
	abstract = {Energy sharing in modular self-reconfigurable robots ensures the energy balance of the modules, thus allowing the system to work sustainably. This paper proposes an energy sharing mechanism for a novel modular self-reconfigurable robot that allows free connections among modules, termed as FreeBOT, such that each FreeBOT can share energy with peers through surface contact. Corresponding energy sharing rules are proposed to achieve an energy sharing network structure without invalid components. As alternative choices, several types of networks subjected to the above requirements are provided, which also maximize the number of FreeBOTs joining to share energy. We implement and test the prototype of the energy sharing mechanism on FreeBOT. The experimental results show that the mechanism can effectively achieve energy sharing among FreeBOTs.},
	keywords = {Automation, Prototypes, Robots},
	isbn = {978-1-7281-9682-4},
	doi = {10.1109/ICRA46639.2022.9811860},
	author = {Guanqi Liang and Yuxiao Tu and Lijun Zong and Junfeng Chen and Tin Lun Lam}
}
@conference {Tu2022,
	title = {FreeSN: A Freeform Strut-node Structured Modular Self-reconfigurable Robot - Design and Implementation},
	booktitle = {2022 International Conference on Robotics and Automation (ICRA)},
	year = {2022},
	pages = {4239{\textendash}4245},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Philadelphia, PA, USA},
	abstract = {This paper proposes a novel freeform strut-node structured modular self-reconfigurable robot (MSRR) called FreeSN, consisting of strut and node modules. A node module is mainly a low-carbon steel spherical shell. A strut module contains two freeform connectors, which provide strong magnetic connections and flexible spherical motions. The FreeSN system shares the benefits of freeform connection and strut-node structures. The freeform connection brings good adaptability to the environment. The triangle substructures inside the system configuration significantly improve the structural stability. The parallel execution of module motions can superpose the module capabilities and makes the system more scalable. The modules can combine these robot features by selecting the system configuration and better fit different circumstances and tasks. Four demonstrations, including assembly, obstacle crossing, transportation, and object manipulation, are designed to show the capabilities of the FreeSN system in different aspects. The results show the great performance and versatility of this MSRR system.},
	keywords = {Automation, Connectors, Robots, Steel, Structural engineering, Task analysis, Transportation},
	isbn = {978-1-7281-9682-4},
	doi = {10.1109/ICRA46639.2022.9811583},
	author = {Yuxiao Tu and Guanqi Liang and Tin Lun Lam}
}
@conference {Tu2021,
	title = {Graph Convolutional Network based Configuration Detection for Freeform Modular Robot Using Magnetic Sensor Array},
	booktitle = {2021 IEEE International Conference on Robotics and Automation (ICRA)},
	year = {2021},
	pages = {4252{\textendash}4258},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Xi{\textquoteright}an, China},
	abstract = {Modular self-reconfigurable robotic (MSRR) systems are potentially more robust and more adaptive than conventional systems. Following our previous work where we proposed a freeform MSRR module called FreeBOT, this paper presents a novel configuration detection system for FreeBOT using a magnetic sensor array. A FreeBOT module can be connected by up to 11 modules, and the proposed configuration detection system can locate a variable number of connection points accurately in real-time. By equipping FreeBOT with 24 magnetic sensors, the magnetic field density produced by magnets and steel spherical shells can be monitored. The connectable area is split into 199 non-uniform regions, including 84 uniform regions. Using a Graph Convolutional Network (GCN) based algorithm, the connection points can be located accurately under ferromagnetic environments. The system can locate a variable number of connection points for such a region division with only single connection point training data. Finally, the localization algorithm can run faster than 40 Hz on FreeBOT. With the real-time configuration detection system, the FreeBOT system has the potential to reconfigure automatically and accurately.},
	keywords = {Conferences, Location awareness, Magnetic sensors, Real-time systems, Robot sensing systems, Steel, Training data},
	isbn = {978-1-7281-9078-5},
	issn = {1050-4729},
	doi = {10.1109/ICRA48506.2021.9561340},
	author = {Yuxiao Tu and Guanqi Liang and Tin Lun Lam}
}
@conference {413,
	title = {AmphiLight: Direct Air-Water Communication with Laser Light},
	booktitle = {17th USENIX Symposium on Networked Systems Design and Implementation (NSDI 20)},
	year = {2020},
	publisher = {USENIX Association},
	organization = {USENIX Association},
	address = {Santa Clara, CA},
	isbn = {978-1-939133-13-7},
	url = {https://www.usenix.org/conference/nsdi20/presentation/carver},
	author = {Charles J. Carver and Zhao Tian and Hongyong Zhang and Kofi M. Odame and Quattrini~Li, Alberto and Xia Zhou}
}
@article {350,
	title = {Persistent and Robust Execution of MAPF Schedules in Warehouses},
	journal = {IEEE Robotics and Automation Letters},
	volume = {4},
	year = {2019},
	month = {Jan-04-2019},
	pages = {1125 - 1131},
	doi = {10.1109/LRA.2019.2894217},
	url = {https://ieeexplore.ieee.org/document/8620328/https://ieeexplore.ieee.org/ielam/7083369/8581687/8620328-aam.pdfhttp://xplorestaging.ieee.org/ielx7/7083369/8581687/08620328.pdf?arnumber=8620328},
	author = {Honig, Wolfgang and Kiesel, Scott and Tinka, Andrew and Durham, Joseph W. and Ayanian, Nora}
}
@conference {365,
	title = {Intelligent Robotic IoT System (IRIS)Testbed},
	booktitle = {2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
	year = {2018},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Madrid},
	doi = {10.1109/IROS.2018.8593636},
	url = {https://ieeexplore.ieee.org/document/8593636/http://xplorestaging.ieee.org/ielx7/8574473/8593358/08593636.pdf?arnumber=8593636},
	author = {Tran, Jason A. and Ghosh, Pradipta and Gu, Yutong and Kim, Richard and D{\textquoteright}Souza, Daniel and Ayanian, Nora and Krishnamachari, Bhaskar}
}
@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 {384,
	title = {Overview: Generalizations of Multi-Agent Path Finding to Real-World Scenarios},
	booktitle = {IJCAI-16 Workshop on Multi-Agent Path Finding (WOMPF)},
	year = {2016},
	keywords = {workshop},
	author = {Hang Ma and Sven Koenig and Nora Ayanian and Liron Cohen and Wolfgang H{\"o}nig and T. K. Satish Kumar and Tansel Uras and Hong Xu and C. Tovey and G. Sharon}
}
@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}
}
@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.}
}
@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.}
}
@article {172,
	title = {Enforcing Network Connectivity in Robot Team Missions},
	journal = {The International Journal of Robotics Research},
	volume = {29},
	year = {2010},
	pages = {460-480},
	abstract = {The growing interest in robot teams for surveillance or rescue missions entails new technological challenges. Robots have to move to complete their tasks while maintaining communication among themselves and with their human operators, in many cases without the aid of a communication infrastructure. Guaranteeing connectivity enables robots to explicitly exchange information needed in collaborative task execution, and allows operators to monitor or manually control any robot at all times. Network paths should be multi-hop, so as not to unnecessarily restrict the team{\textquoteright}s range. In this work we contribute a complete system which integrates three research aspects, usually studied separately, to achieve these characteristics: a multi-robot cooperative motion control technique based on a virtual spring{\textemdash}damper model which prevents communication network splits, a task allocation algorithm that takes advantage of network link information in order to ensure autonomous mission completion, and a network layer which works over wireless 802.11 devices, capable of sustaining hard real-time traffic and changing topologies. Link quality among peers is the key metric used to cooperatively move the robots and maintain uninterrupted connectivity, and the basis for novel ideas presented in each subsystem. Simulations and experimental results with real robots are presented and discussed.},
	doi = {10.1177/0278364909358274},
	url = {http://ijr.sagepub.com/content/29/4/460.abstract},
	author = {Tardioli, D. and Mosteo, A.R. and Riazuelo, L. and Villarroel, J.L. and Montano, L.}
}
@conference {174,
	title = {Auction-Based Multi-Robot Routing},
	booktitle = {Proceedings of Robotics: Science and Systems},
	year = {2005},
	month = {June},
	address = {Cambridge, USA},
	author = {Michail G. Lagoudakis and Evangelos Markakis and David Kempe and Pinar Keskinocak and Anton Kleywegt and Sven Koenig and Craig Tovey and Adam Meyerson and Sonal Jain}
}
