Abstract
This paper describes a method for sensor data fusion of thermal imaging sensor and a vision system such as a camera for probabilistic target tracking for autonomous robots. Person tracking is a crucial issue for achieving tasks for communication with people and following the target person by the robots. The integration of multiple kinds of sensor data for validation of the recognition result is desirable because of the uncertainty of recognition results based on the vision system. We use a stochastic model based on asynchronous updating the model of the tracking target by measurement data of the camera and the thermal imaging sensor. Experimental results indicate the feasibility of the proposed method.
