Title :
Indoor robot localization by RSSI/IMU sensor fusion
Author :
Malyavej, Veerachai ; Kumkeaw, Warapon ; Aorpimai, Manop
Author_Institution :
Dept. of Control, Instrum. & Mechatron., Mahanakorn Univ. of Technol., Bangkok, Thailand
Abstract :
Localization is the crucial problem for mobile robot navigation. For indoor mobile robot, since a global positioning system (GPS) is incapable, another promising technique to detect the position is the received signal strength indicator (RSSI) from wireless communication. To improve the precision and robustness of mobile unit localization, an inertial measurement unit (IMU) is normally used. In this report, we propose the algorithm for mobile robot localization based on sensor fusion between RSSI from wireless local area network (WLAN) and an IMU. The proposed fusion scheme is based on the extended Kalman filter (EKF). The experiment is conducted by using mobile unit equipped with low-cost IMU and a wireless communication module together with access points to evaluate the performance of our algorithm, and the result is promising.
Keywords :
Kalman filters; control engineering computing; mobile robots; path planning; sensor fusion; wireless LAN; Global Positioning System; RSSI-IMU sensor fusion; WLAN; extended Kalman filter; indoor robot localization; inertial measurement unit; mobile robot navigation; received signal strength indicator; wireless communication; wireless local area network; Kalman filters; Mathematical model; Mobile communication; Noise; Robot sensing systems; Sensor fusion; Wireless communication; IMU; Kalman Filter; Localization; RSSI;
Conference_Titel :
Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2013 10th International Conference on
Conference_Location :
Krabi
Print_ISBN :
978-1-4799-0546-1
DOI :
10.1109/ECTICon.2013.6559517