Online Feature Weighting for Human Discrimination in a Person Following Robot

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.

Palabras clave: feature weighting, person follower, guide robot