Extended Kalman Filter Based Mobile Robot Localization in Indoor Fire Environments

Jong-Hwan Kim and Gun In Kim
Mechanical & Systems Engineering, Korea Military Academy, Seoul, Republic of Korea
Abstract—This paper presents localization of a mobile firefighting robot. Sensors that have been widely used for the localization in the past have shown limitations under fire environments due to low visibility and high temperatures. The extended Kalman filter was designed to accurately estimate position and orientation of the robot using relative distances to walls or objects surroundings. In addition, data from a Frequency-Modulated Continuous-Wave (FMCW) Radar, Inertial Measurement Unit (IMU) and encoders that are capable of withstanding fire environments were fused to localize the robot in indoor fire environments. For its validation, an experiment was conducted in a 2 m × 4 m area. The experimental results showed that the proposed localization method was reliable. 

Index Terms—firefighting robot, localization, multi-sensor fusion, fire environments, mobile robot

Cite: Jong-Hwan Kim and Gun In Kim, "Extended Kalman Filter Based Mobile Robot Localization in Indoor Fire Environments," International Journal of Mechanical Engineering and Robotics Research, Vol. 5, No. 1, pp. 62-66, January 2016. DOI: 10.18178/ijmerr.5.1.62-66
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