@conference {441,
	title = {DeepURL: Deep Pose Estimation Framework for Underwater Relative Localization},
	booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
	year = {2020},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Las Vegas, NV, USA},
	doi = {10.1109/IROS45743.202010.1109/IROS45743.2020.9341201},
	url = {https://ieeexplore.ieee.org/document/9341201/},
	author = {Joshi, Bharat and Modasshir, Md and Manderson, Travis and Damron, Hunter and Xanthidis, Marios and Quattrini~Li, Alberto and Rekleitis, Ioannis and Dudek, Gregory}
}
@article {425,
	title = {Robust Asymptotic and Finite-time Tracking for Second-order Nonlinear Multi-agent Autonomous Systems},
	journal = {International Journal of Control Automation and Systems},
	volume = {17},
	year = {2019},
	month = {12/2019},
	type = {Research },
	chapter = {3069},
	abstract = {This paper investigates consensus based distributed robust asymptotic and finite-time tracking control strategy for second-order multi-agent autonomous systems. The protocol design uses states of the neighboring agents with directed communication topology in the presence of uncertainty associated with the autonomous agents. Robust adaptive learning algorithm uses with the protocol design for each follower agent to learn and adapt bounded uncertainty associated with nonlinear dynamics of the follower agents. Adaptive learning protocol also integrates with the follower agents protocol to learn and adapt bounded input of the leader. Lyapunov method with Graph, classical sliding mode, and terminal sliding mode theory use to guarantee that the proposed distributed control design can reach an agreement and follow the states of the leader in both finite-time and asymptotic sense. Analysis shows that consensus based protocol can force the states of the followers sliding surface to track the states of the leader sliding surface in finite-time and remain there. The proposed distributed consensus protocol does not require the exact bound of the uncertainty associated with the follower agents. Also, the proposed protocol does not require the exact bound of the leader input as opposed to other distributed cooperative control designs. Evaluation results with comparison are presented to demonstrate the validity of the theoretical argument for the real-time applications.},
	author = {Shafiqul Islam and Nicolas Xiros}
}
@article {353,
	title = {Overview: A Hierarchical Framework for Plan Generation and Execution in Multirobot Systems},
	journal = {IEEE Intelligent Systems},
	volume = {32},
	year = {2017},
	month = {Jan-11-2017},
	pages = {6 - 12},
	issn = {1541-1672},
	doi = {10.1109/MIS.2017.4531217},
	url = {http://ieeexplore.ieee.org/document/8268002/http://xplorestaging.ieee.org/ielx7/9670/8267591/08268002.pdf?arnumber=8268002},
	author = {Ma, Hang and Honig, Wolfgang and Cohen, Liron and Uras, Tansel and Xu, Hong and Kumar, T.K. Satish and Ayanian, Nora and Koenig, Sven}
}
@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 {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 {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 {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}
}
