Kalman filter and NARX neural network for robot vision based human tracking
Emina Petrović, Žarko Ćojbašić, Danijela Ristić–Durrant, Vlastimir Nikolić, Ivan S Ciric, Srđan Matić · SCIndeks · 2013
Tracking human is an important and challenging problem in video-based intelligent robot systems. In this paper, a vision-based human tracking system is supposed to provide sensor input for vision-based control of a mobile robot that works in a team helping the human co-worker. A comparison between NARX neural network and Kalman filter in solving the prediction problem of human tracking in robot vision is presented. After collecting video data from a robot, simulation results obtained from the Kalman filter model are used to compare with the simulation results obtained from the NARX Neural network.