Robots are rapidly evolving from factory workhorses, which are physically bound to their work-cells, to increasingly complex machines capable of performing challenging tasks in our daily environment. The objective of this course is to provide the basic concepts and algorithms required to develop mobile robots that act autonomously in complex environments. The main emphasis is put on mobile robot locomotion and kinematics, environment perception, probabilistic map based localization and mapping, and motion planning. The textbook Introduction to Autonomous Mobile Robots by Roland Siegwart, Illah Nourbakhsh, Davide Scaramuzza, The MIT Press, second edition 2011.
You have a very good localization method, called Kalman filer, it works with a single sensor and many sensors as well. You have also particule filter and many others based on estimation theory. But be aware that these methods are merely data fusion algorithms, that means that the real localization starts with sensors, imu, odometry, lidar, ultrasonic, and vision sensors so it is a big problem in the world of robotics.