Colour plays a fundamental role in the per-
ception process of humans. In robotics, the exploita-
tion of this type of information has become increas-
ingly important in many different tasks. The develop-
ment of new sensors has made it possible to obtain
colour information together with depth information
about the environment. We have recently developed a
scan matching algorithm based on evolutionary con-
cepts (Differential Evolution). The main objective of
this work is to include colour properties in the reg-
istration process, studying how colour can be used
to improve the scan matching process. In particular,
we have designed a filter to extract the most signif-
icant points of a RGB-D scan based on the Delta E
divergence between neighbours. In addition, colour
properties have also been included in the fitness func-
tion of the scan matching method. Our approach has
been tested in a real environment and the most signif-
icant conclusion is the improvement of the algorithm
performance when measuring the valley of conver-
gence.