On Simultaneous Localization And Map-Building Of Mobile Robots

With the development of computer technology, artificial intelligence technology, control technology and sensor technology, mobile robot technology is developing very fast in recent years. As a hot topic in the field of mobile robot, simultaneous localization and map-building is considered to be the key technique for autonomous to mobile robot, and it has significant theoretical and application value.In this thesis, the simultaneous localization and map-building for mobile robot is studied. For some existed problems of the standard EKF-SLAM algorithm, this thesis has proposed an improved EKF-SLAM algorithm based on constrained observation range. The main contents and achievements are listed as follows:1. The mathematical model of SLAM problem is analyzed, and the related models for SLAM problem are defined.2. The EKF-SLAM and UKF-SLAM algorithms are introduced and discussed, and then, comparison studies are carried out for these two typical SLAM algorithms on the localization accuracy.3. An improved EKF-SLAM algorithm based on constrained observation range is proposed in this thesis. Due to the fact that the standard EKF-SLAM algorithm has some limitations, such as high computational and low localization accuracy, we have obtained the improved EKF-SLAM algorithm by adding constraints to the observation range of the robot and deleting the match landmarks which exceed the constrained range in the system state vector. Finally, the improved EKF-SLAM algorithm and the standard EKF-SLAM, UKF-SLAM algorithm are compared by simulation experiments, which shows that our improved EKF-SLAM algorithm achieves a better performance on efficiency and localization accuracy.