Abstract
A robust and adaptive person-following behaviour is an important ability that most service robots must have to be able to face challenging illumination conditions, and crowded spaces of non-structured environments. In this paper, we propose a system which combines a laser based tracker with the support of a camera, acting as a discriminator between the target, and the other people present in the scene which might cause the laser tracker to fail. The discrimination is done using a online weighting of the feature space, based on the discriminability of each feature analysed.
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Alvarez-Santos, V., Pardo, X.M., Iglesias, R., Canedo-Rodriguez, A., Regueiro, C.V. (2011). Online Feature Weighting for Human Discrimination in a Person Following Robot. In: Ferrández, J.M., Álvarez Sánchez, J.R., de la Paz, F., Toledo, F.J. (eds) Foundations on Natural and Artificial Computation. IWINAC 2011. Lecture Notes in Computer Science, vol 6686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21344-1_24
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DOI: https://doi.org/10.1007/978-3-642-21344-1_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21343-4
Online ISBN: 978-3-642-21344-1
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