The Comparison of Estimation Algorithms for Mobile Robot Navigation

Abstract

In this study, a robot with different maneuvras is followed with different estimation algorithms. The mobile robot has acted first linear, then maneuver and finally linear again. It's speed is constant through the way. Standard Kalman Filter, Adaptive Kalman Filter, Extended Kalman Filter and Interacting Multiple Model consist of multiple model Kalman Filter combined of linear and non-linear model are used to follow the act of the robot. The results of these estimations are compared with each other. Multiple model Kalman Filter is the best estimation algorithm among them for this motion model.