Abstract
Bearing-only Simultaneous Localization and Mapping (SLAM) is a partially observable SLAM problem, in wich the sensor used for perceiving the robot‘s enviroment, provides only-angular information respect to the landmarks, and therefore does not give enough information to compute the full state of a landmark from a single observation. In this context, vision-based systems have also gained a great interest in the robotics community. Nevertheless the use of “sound sources” as map’s features have been very little explored in SLAM. In this work a method for performing SLAM with sound sources is presented. A robot capable of sense bearing information respect to an external sound source with modest angular acuity ( − 10°) is considered.At the robot trajectory start, the sound source position is unknown; while the robot moves, the position of the sound source and the robot position in a global coordinate frame are both estimated. Experimental results with simulations and with a real robot demonstrate that tracking a unique source sound is enough to reasonably correct the odometry information provided by the encoders.
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© 2008 Springer-Verlag Berlin Heidelberg
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Munguía, R., Grau, A. (2008). Single Sound Source SLAM. In: Ruiz-Shulcloper, J., Kropatsch, W.G. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2008. Lecture Notes in Computer Science, vol 5197. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85920-8_9
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DOI: https://doi.org/10.1007/978-3-540-85920-8_9
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