@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}
}
