High-accuracy global localization filter for three-dimensional environments

The localization problem in mobile robotics can be defined as the search of the robot's coordinates in a known environment. If there is no information about the initial location, we are talking about global localization. In this work, we have developed an algorithm that solves this problem in a three-dimensional (3D) environment using evolutionary computation concepts. The method has been called RELF-3D and has many features that make it very robust and reliable: thresholding and discarding mechanisms, different cost functions, effective convergence criteria, and so on. The resulting global localization module has been tested in numerous experiments and the most important improvement obtained is the accuracy of the method, allowing its application in manipulation tasks.