ROS Based Mobile Robot Navigation with Imperfect Data Association

This paper attempts to design and analyze a mobile robot navigation system with imperfect data association. In this paper, we address the issue related to navigation and control of a mobile robot which enable it to deal with unexpected moving obstacles by sensor-based control. A probabilistic approach is proposed to deal with collision avoidance under certain uncertainty conditions. The mobile robot localization methodologies in common use at present will be introduced. A localization algorithm based on Extended Kalman Filter (EKF) will be the technique to be investigate considering of environment feature extraction and map building. The technique can reduce the error in the calculation of the robot`s position and orientation. The analysis is mainly taken into account the observations about the mobile robot surroundings from multiple sensors by EKF, which enables the robot to identify the surrounding objects clearly and moves accordingly. The simulation results show that the proposed navigation method is effective to estimate the mobile robot location with imperfect data association.