First results in the development of a mobile robot with trajectory planning and object recognition capabilities

Talgat Islamgozhayev 1 , Maksat Kalimoldayev 1 , Arman Eleusinov 1 , Shokan Mazhitov 1 , and Orken Mamyrbayev 1
  • 1 Institute of Information and Computational Technologies, Almaty, Kazakhstan


The use of mobile robots is becoming popular in many areas of service because they ensure safety and good performance while working in dangerous or unreachable locations. Areas of application of mobile robots differ from educational research to detection of bombs and their disposal. Based on the mission of the robot they have different configurations and abilities – some of them have additional arms, cranes and other tools, others use sensors and built-in image processing and object recognition systems to perform their missions. The robot that is described in this paper is mobile robot with a turret mounted on top of it. Different approaches have been tested while searching for best method suitable for image processing and template matching goals. Based on the information from image processing unit the system executes appropriate actions for planning motions and trajectory of the mobile robot.

If the inline PDF is not rendering correctly, you can download the PDF file here.

  • [1] Weyrich M., Laurowski M., Klein P., Wang Y., High speed vision based automatic inspection and path planning for processing conveyed objects, Procedia CIRP, 2012, 3, 442–447

  • [2] Mohammed A., Wang L., Gao R., Integrated image processing and path planning for robotic sketching, Procedia CIRP, 2013, 12, 199–204

  • [3] Lemaire T., Berger C., Jung I., Lacroix S., Vision-based SLAM: stereo and monocular approaches, Int J Comput Vision, 2007, 74(3), 343–364

  • [4] Boyko I.A., Guryanov R.A., Recognition of objects based on the video obtained from camera mounted on a mobile platform, Young scientist, 2013, 6, 26–34 (Russian)

  • [5] LaValle S.M., Planning algorithms, Cambridge University Press, Cambridge, 2006

  • [6] Weibo W., Study on automatic object detection and tracking based on image, Nanjing University of Science and Technology, Nanjing, Jiangsu, China, 2006

  • [7] Hao Z., Zhu M., Design and implementation of target intelligent detecting and tracking system, Opto-Electronic Engineering, 2007, 34(1), 27–31

  • [8] Abramov N.S., Romankin V.A., Methods of control of rotating video camera (in Russian), Izvestiya SFedU, Engineering Sciences, 2013, 7(144), 173–179

  • [9] Aleksandrov P.S., Lectures on Analytical Geometry (in Russian), Nauka, Moscow, 1968

  • [10] Vygodsky M., Mathematical Handbook: Higher Mathematics, Mir Publishers, Moscow, 1975

  • [11] Martin J., Crowley J.L., Experimental Comparison of correlation techniques, In: Proceedings of the Conference on Intelligent Autonomous Systems (March 1995, Karlsruhe, Germany), IAS ’95, 1995, 86–93

  • [12] Pollefeys M., Nister D., Detailed real-time urban 3D reconstruction from video, IJCV, 2008, 78, no. 2–3, 143–167

  • [13] Wen Chung C., Shu-An L., Real-time feature-based 3D map reconstruction for stereo visual guidance and control of mobile robots in indoor environments, In: Proceedings of 2004 IEEE International Conference on Systems,Man and Cybernetics (10-13 October 2005, Hague, Netherlands), IEEE Xplore 2005, vol. 6, 5386–5391

  • [14] Wang P.K.C., Hadaegh F.Y., Lau K., Synchronized formation rotation and attitude control of multiple free-flying spacecraft, AIAA J. Guidance, Contr. Dynamics, 1999, 22(1), 28–35

  • [15] Ren W., Sorensen N., Distributed coordination architecture for multi-robot formation control, Robot. Auton. Syst., 2008, 56, 324–333


Journal + Issues