A Solution to Active Simultaneous Localization and Mapping Problem Based on Optimal Control

Abstract

In this paper, the method for the simultaneous localization and mapping (SLAM) problem based on extended Kalman filter (EKF) is introduced. Then a strategy of active SLAM using optimal control is proposed. In our method, the accuracy and integrity of localization and mapping constitute the objective function. The robot executes the control inputs which can optimize the function in order to implement simultaneous localization and mapping in an active, intelligent and adaptive way. Finally, simulation results are given for validation and it is shown that our method leads to more accurate estimation and higher efficiency as compared to the traditional random motion.