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@InProceedings{RWSN09-jung,
	author="Tobias Jung and Mazda Ahmadi and Peter Stone",
	title="Connectivity-based Localization in Robot Networks",
	booktitle="International Workshop on Robotic Wireless Sensor Networks (IEEE DCOSS '09)",
	month="June",
	year="2009",
	abstract={
		Consider a small team of autononomous robots, each equipped
		with a radio, that are deployed in an ad-hoc fashion and whose goal it
		is to act as signal relay nodes to form a temporary, adaptive, and
		highly robust communication network. To perform this type of
		self-optimization and self-healing, relative localization (i.e. knowing
		direction and distance to every other robot in the network) is
		necessary. In a sense, the problem is similar to the one studied in
		ad-hoc sensor networks. The key differences are that (1) anchor nodes
		with known locations are not available; that (2) the connectivity graph
		is very sparse, because of a comparatively small number of nodes
		involved; and that (3) the communication nodes are actually mobile
		robots such that apart from location we also have to estimate the
		directions to other nodes (which can not be obtained from a single time
		slice). To solve this problem, we propose a global approach that
		exploits the mobility of the robots to obtain multiple connectivity
		measurements over a small time window. Together with the odometry of
		individual robots, we then try to estimate underlying locations that
		best explain the observerd connectivity data by minimizing a suitable
		stress function. Through simulation of a concrete real-world scenario we
		show that our approach performs reasonably well with as few as ten
		robots. We examine its performance both under outdoor and indoor
		conditions (i.e. uniform and non-uniform signal propagation). In
		addition, we also consider the case where we are able to observe the
		distance between connected tobots, which further improves accuracy
		substantially.
	},
}