A Novel Infrared Navigational Algorithm for Autonomous Robots

This paper contains a hybridization technique of an Odometer (Odom) and an Inertial Navigation System (INS). The originality lies in the formulation of the odometer integrated by a Novel Infrared Navigational Algorithm (NIRNA) to build the system (Odom/INS) proposed. NIRNA, an algorithm for sensor fusion and navigation, is presented and its integration introduced to build Odom/INS system. In addition, the kinematic of the 4 wheeled mobile robot is study to consider two localization techniques based on (Inertial Measurement Units (IMU) and Odometer). The whole system built integrates the two localization techniques and use an Integrated Kalman Filter (IKF) as data fusion module in order to improve the estimated output of the whole system. Two simulation tests are conducted to evaluate the built system's performance. As fusion algorithm, Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF) are used (in turn) in the IKF module to investigate the robustness and accuracy of the built hybrid system and later compare their implementation results. The simulation results show that the proposed system is feasible and reliable and its implementation with NIRNA outperforms that of some existent navigation algorithms such as HCTNav. That is confirmed by the resulting results that the implementation with NIRNA presents higher accuracy estimation and lower mean-square error (MSE) for mobile robot state than for instance, the implementation with HCTNav.