Mobile Robot Indoor Localization Using Color-Coded Beacons and a Depth Camera

Year 2022, Volume: 17 Issue: 1, 37 - 46, 20.03.2022

Mawj Mohammed Basheer , Mehmet Çavaş Mohammed Qasım

https://doi.org/10.55525/tjst.1054213

Abstract

This paper aims to design and implement an indoor localization method for mobile robots based on trilateration technique, Color Code signatures (CCs) as artificial passive beacons, and a depth camera. The artificial passive beacons are designed as three disks positioned one on top of the other’s with different sizes and colors (primary colors only, RGB). The three disks share the same center. The designed beacons are placed on the ceiling to be visible from most locations within the room. The robot's model, controller, and localization method are implemented and evaluated inside the CoppeliaSim environment. The simulation results show that the CCs detecting algorithm enables the robot to discover the designed beacons, achieve an accurate localization and reach the target

Keywords

Omnidirectional robot, CoppeliaSim program, Trilateration., localization

References

• [1] Fabregas, E., Farias, G., Peralta, E., Vargas, H. & Dormido, S. Teaching control in mobile robotics with V-REP and a Khepera IV library. In 2016 IEEE conference on control applications.2016. IEEE. pp.821-826.
• [2] Francisco R., Francisco V. and Carlos L.A.,. A review of mobile robots: Concepts, methods, theoretical framework, and applications. International Journal of Advanced Robotic Systems.2019. 16(2).1-22
• [3] Pablo, C., Miguel, V., David, C., Luis, M. and Manuel, B., Indoor Robot Positioning using an Enhanced Trilateration Algorithm. Engineering and Industrial Development Center (CIDESI).2016. 13(3).1-8
• [4] Chuang, L. Object localisation strategy for a mobile robot using RFID.2012. 1(1). 5.
• [5] Gueaieb, W., and Miah, M.S. An intelligent mobile robot navigation technique using RFID technology. IEEE Transactions on Instrumentation and Measurement.2008. 57(9), pp. 1908-1917.
• [6] Mohanad, N. N., Mohammed, Q., and Omar, Y. I. Landmarks exploration algorithm for mobile robot indoor localization using vision sensor. Journal of Engineering Science and Technology. 2021. 16(4). pp. 3165 – 3184.
• [7] Ladd, A.M., Bekris, K.E., Rudys, A.P., Wallach, D.S. and Kavraki, L.E. On the feasibility of using wireless ethernet for indoor localisation. IEEE Transactions on Robotics and Automation.2004. 20(3), pp. 555-559.
• [8] Felipe, P. C., Joao, A. F., and Andre S. O. Integrating mobile robot navigation control, visual object detection and manipulation using ROS and V-REP. Conference: Congresso Brasileiro de Inteligência Computacional.2020.134(10).5.
• [9] Bittel, O. and Blaich, M. Mobile robot localisation using beacons and the Kalman filter technique for the Eurobot competition. International Conference on Research and Education in Robotics. Springer.2011.pp. 55-67.
• [10] Huosheng, H., and Dongbing, G. Landmark-based navigation of industrial mobile robots. Industrial Robot- an International Journal.2000.27 (6). pp. 458-467.