|Farnaz Adib Yaghmaei|
Developing Methods for SLAM in Dynamic Environment with Grid Based Map
In this thesis two new methods for navigation in dynamic environment are introduced based on force field approach. In these approaches it is assumed that the unknown trajectory of dynamic obstacle is predicted by Kalman Filter. The mobile robot avoids colliding the moving object by using the two proposed methods of potential ban or escaping algorithm. In these methods, robot navigates through static and dynamic objects without any predefined information about their motion. The motion of each moving object is predicted by a Kalman filter, and the force field map is generated and updated for the robot to navigate among static and dynamic obstacles. Finally, a cost function based on minmax theory is defined to measure the performance of different methods, and it is shown through different experiments that the proposed method is out performing traditional approaches.