Single-Sensor Probabilistic Localization on the SeReS Self-Reconfigurable Robot

Kenneth Payne, Jacob Everist, Feili Hou, and Wei-Min Shen. Single-Sensor Probabilistic Localization on the SeReS Self-Reconfigurable Robot. In The 9th Intl. Conf. Intelligent and Autonomous Systems (IAS-9), Tokyo, Japan, March 2006.

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Abstract

This paper proposes a novel method for localizing a stationary infrared source of unknown orientation relative to a static docking sensor. This method uses elliptical approximations of likely positions of the infrared source and computes the intersections to find the most probable locations. It takes only a few samples to localize, is easily computed with inexpensive microcontrollers, and is robust to sensor noise. We then compare our approach with two other methods. The first uses a Bayesian filter across a map of discrete locations in the robot's operational workspace to determine the suspected source position. The second also uses a probability distribution map but uses the method described by Elfes in his paper on probabilistic sonar-based mapping and navigation [1]. We show that our approach localizes quickly with a single sensor and is no more computationally demanding than other methods.

BibTeX Entry

@InProceedings{	  payne2006single-sensor-probabilistic-localization-on-the-seres,
  abstract	= {This paper proposes a novel method for localizing a
		  stationary infrared source of unknown orientation relative
		  to a static docking sensor. This method uses elliptical
		  approximations of likely positions of the infrared source
		  and computes the intersections to find the most probable
		  locations. It takes only a few samples to localize, is
		  easily computed with inexpensive microcontrollers, and is
		  robust to sensor noise. We then compare our approach with
		  two other methods. The first uses a Bayesian filter across
		  a map of discrete locations in the robot's operational
		  workspace to determine the suspected source position. The
		  second also uses a probability distribution map but uses
		  the method described by Elfes in his paper on probabilistic
		  sonar-based mapping and navigation [1]. We show that our
		  approach localizes quickly with a single sensor and is no
		  more computationally demanding than other methods. },
  address	= {Tokyo, Japan},
  author	= {Kenneth Payne and Jacob Everist and Feili Hou and Wei-Min
		  Shen},
  booktitle	= {The 9th Intl.\ Conf.\ Intelligent and Autonomous Systems
		  (IAS-9)},
  month		= {March},
  title		= {Single-Sensor Probabilistic Localization on the {SeReS}
		  Self-Reconfigurable Robot},
  year		= {2006}
}