Author(s):
1. Ivan Ćirić, Faculty of Mechanical Engineering in Niš, Serbia
2. Žarko Ćojbašić, Faculty of Mechanical Engineering in Niš, Serbia
3. Vlastimir Nikolic, Faculty of Mechanical Engineering in Niš, Serbia
4. Milica Ćirić, Faculty of Civil Engineering and Architecture in Niš, Serbia
5. Mladen Tomić, The School of Higher Technical Professional Education, Niš, Serbia
6. Emina Petrovic, Faculty of Mechanical Engineering in Niš, Serbia
7. Miloš Simonović, Faculty of Mechanical Engineering in Niš, Serbia

Abstract:
This paper addresses an important and challenging problem of real‐time vision‐based human tracking to enable mobile robots to follow a human and help him as a co-worker in hazardous environment. A novel approach that combines intelligent stereo vision‐based human detection with neural network estimator that helps tracking is presented. Stereo vision‐based detection combines features extracted from 2D stereo images with intelligent classification algorithms to detect humans in a robot’s environment. Prediction of the 3D coordinates of a human in the robot’s camera coordinate system based on recurrent neural network reduces image region of interest and ensures more reliable human tracking. Within a working scenario of a mobile robot intended to follow a human co‐worker in indoor applications, collected video data will be collected and compared with simulation results obtained from the recurrent neural network.

Key words:
robot vision,mobile robotics,neural networks,human tracking

Thematic field:
Mechatronics and Information Technology

Date of abstract submission:
07.03.2015.

Conference:
12th International conference on accomplishments in Electrical and Mechanical Engineering and Information Technology (DEMI 2015)

Final paper