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Sensors 2013, 13(1), 1268-1299; doi:10.3390/s130101268
Article

Robot Evolutionary Localization Based on Attentive Visual Short-Term Memory

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Received: 22 December 2012; in revised form: 14 January 2013 / Accepted: 14 January 2013 / Published: 21 January 2013
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Abstract: Cameras are one of the most relevant sensors in autonomous robots. However, two of their challenges are to extract useful information from captured images, and to manage the small field of view of regular cameras. This paper proposes implementing a dynamic visual memory to store the information gathered from a moving camera on board a robot, followed by an attention system to choose where to look with this mobile camera, and a visual localization algorithm that incorporates this visual memory. The visual memory is a collection of relevant task-oriented objects and 3D segments, and its scope is wider than the current camera field of view. The attention module takes into account the need to reobserve objects in the visual memory and the need to explore new areas. The visual memory is useful also in localization tasks, as it provides more information about robot surroundings than the current instantaneous image. This visual system is intended as underlying technology for service robot applications in real people’s homes. Several experiments have been carried out, both with simulated and real Pioneer and Nao robots, to validate the system and each of its components in office scenarios.
Keywords: visual attention; object tracking; active vision; visual localization visual attention; object tracking; active vision; visual localization
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Vega, J.; Perdices, E.; Cañas, J.M. Robot Evolutionary Localization Based on Attentive Visual Short-Term Memory. Sensors 2013, 13, 1268-1299.

AMA Style

Vega J, Perdices E, Cañas JM. Robot Evolutionary Localization Based on Attentive Visual Short-Term Memory. Sensors. 2013; 13(1):1268-1299.

Chicago/Turabian Style

Vega, Julio; Perdices, Eduardo; Cañas, José M. 2013. "Robot Evolutionary Localization Based on Attentive Visual Short-Term Memory." Sensors 13, no. 1: 1268-1299.



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