Luu Trong Hieu * and Tran Thanh Hung

* Correspondence: Luu Trong Hieu (email:

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This paper proposes a method for controlling a mobile robot using decentralized control based on signal from ceiling camera to remotely recognize simulated chemicals by color sensing. This camera recognizes a robot tag, which put on the robot, to specify the coordinate of the target and sends back to master computer. Based on this signal, the master computer controls the robot to the central of the coordinate where a chemical is put. Whenever moving to the expected position, the robot will open the gripper and grip the target. A slave computer analyzes the signal from an on-board spectrometer to recognize the target and send the result to the master one’s. Experiment results are proved to the applying ability of mobile robots to identify unknown targets.
Keywords: Camera coordinates, decentralized control, mobile robot, onboard spectrometer, robot’s tag, simulated chemicals

Article Details


Anderson, G., Sheesley, C., Tolson, J., Widson, E., Tunstel, E., 2006. A mobile robot system for remote measurements of ammonia vapor in the atmosphere. In Proceedings of IEEE conference on Systems, Man and Cybernetics, 2006 (SMC ’06) in Taipei, Taiwan, 08-11 October 2006.1: 241-246.

Eiceman, G.A., Wang, M., Prasad, S., Schmidt, H., Tadjimukhamedov, F.K., Lavine, B.K., Mirjankarb, N., 2006. Pattern recognition analysis of differential mobility spectra with classification by chemical family. Analytica Chimica Acta. 579: 1-10.

Hieu, T.L., Hung, T.T., 2015. 3D Vision for Mobile Robot Manipulator on Detecting and Tracking Target. In Proceedings of 15th IEEE international conference on control, automation and systems (ICCAS), 2015 in Busan, Korea, 13-16 October 2015, 1560-1565.

Kuzniz, T., Halot, D., Mignani, A.G., Ciaccheri, L., Kalli, K., Tur, M., Othonos, A., Christofides, C., Jackson, D.A., 2007. Instrumentation for the monitoring of toxic pollutants in water resources by means of neural network analysis of absorption and fluorescence spectra. Sensors and Actuators B: Chemical. 121: 231-237.

Lyons, W.B., Fitzpatrick, C., Flanagan, C., Lewis, E., 2004. A novel multipoint luminescent coated ultra violet fiber sensor utilizing artificial neural network pattern recognition techniques. Sensors and Actuators A: Physical. 115: 267-272.

Papadias, D., Theodoridis, Y., 1997. Spatial relations, minimum bounding rectangles, and spatial data structures. International Journal of Geographical Information Science. 2:111-138.

Pulido, C., Esteban, O., 2010. Improved fluorescence signal with tapered polymer optical fibers under side-illumination. Sensor and Actuators B: Chemical.146: 190-194.

Ross, S.M., 2009. Introduction to probability and statics for engineers and scientists, Fourth Edition. Elsevier, 640 pages.

Suah, F.B.M., Ahmad, M., Taib, M.N., 2003. Applications of artificial neural network on signal processing of optical fiber pH sensor based on bromophenol blue doped with sol-gel film. Sensors and Actuators B: Chemical. 90: 182-188.