Localization in 3D environments using differential, evolution

It is necessary to determine the robot's pose to localize a mobile robot in a known environment. If there is no information about the initial location, we are talking about global localization. In our previous work we solved this problem in a two-dimensional environment with an algorithm known as Evolutive Localization Filter (ELF). Based on evolutionary computation concepts, the proposed algorithm searches stochastically along the state space for the robot's best pose estimate. In this paper we have improved our method designing an algorithm with new features, called ELF-3D, that uses three-dimensional sensorial information. The resulting global localization module has been tested in a simulated indoor environment. The most important improvement obtained is the accuracy of the method, allowing to apply it in manipulation tasks.