Autonomous Integrated Navigation for Indoor Robots Utilizing On-Line Iterated Extended Rauch-Tung-Striebel Smoothing

Abstract

In order to reduce the estimated errors of the inertial navigation system (INS)/Wireless sensor network (WSN)-integrated navigation for mobile robots indoors, this work proposes an on-line iterated extended Rauch-Tung-Striebel smoothing (IERTSS) utilizing inertial measuring units (IMUs) and an ultrasonic positioning system. In this mode, an iterated Extended Kalman filter (IEKF) is used in forward data processing of the Extended Rauch-Tung-Striebel smoothing (ERTSS) to improve the accuracy of the filtering output for the smoother. Furthermore, in order to achieve the on-line smoothing, IERTSS is embedded into the average filter. For verification, a real indoor test has been done to assess the performance of the proposed method. The results show that the proposed method is effective in reducing the errors compared with the conventional schemes.