Improved Navigation System of Marine Unmanned Robot Based on Sensor Fusion

Abstract

Improving navigation systems for Unmanned marine robots is one of the challenging issues in recent decades. In this paper, an Unmanned Surface Vehicle (USV) is introduced, which has an improved navigation system to carry out various missions in the sea. This marine robot works with sea waves and solar energy. Robot's navigation includes a global navigation satellite system (GNSS), and a compass sensor. Also, an algorithm is designed to improve navigation, which combines sensor information with classical filters such as Extended Kalman Filter (EKF) and Particle Filter (PF). Finally, the simulation results showed that EKF and PF filters have very similar and acceptable results in determining the robot's position. In the implementation, by implementing EKF on the USV control board, the information combination of sensors based on EKF was investigated and achieved higher accuracy than GNSS.