Development of Line Follower Robot with Camera Surveillance System
W.H.M. Saad1, H.R. Ramli2, R. Marimuthu3, S.A.A Karim4, Z. Manap5
1W.H.M. Saad*, Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer, Centre for Telecommunication Research & Innovation Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia.
2H.R. Ramli, Faculty Engineering, University Putra Malaysia, Serdang, Selangor, Malaysia.
3R. Marimuthu, Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia.
4S.A.A Karim, Department of Electrical Engineering, Politeknik Ibrahim Sultan, Pasir Gudang, Johor, Malaysia.
5Z. Manap, Fakulti Teknologi Kejuruteraan Elektri dan Elektronik, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia. 

Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 2192-2197 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7861118419/2019©BEIESP | DOI: 10.35940/ijrte.D7861.118419

Open Access | Ethics and Policies | Cite  | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: This study describes the development of a line follower robot for a surveillance camera monitoring system. An effective closed loop control fuzzy logic algorithm is used to constantly correct wrong movements of the mobile robot using a feedback mechanism. The robot senses a black line on a white surface and endeavors itself accordingly to follow the track. A manual navigation system has also been designed to overrule the automatic navigation control of the robot to reposition itself back on the track whenever it strays from the path unintentionally. The fuzzy controller algorithm is an advanced method to ensure the line follower robot moves accurately on the track. It is a replacement control technique of traditional switching method. To fuzzifying the digital input data of four infrared sensor that detecting the line, the data is converted into error and delta error that represent the current and previous position of the robot relative to the line that it follows. There are nine base rules that have been created with two inputs which are error and delta error to the robot direction whether to go to the right, move forward or to the left. Then, for defuzzification, center of sum and centroid of area method have been used to calculate the defuzzied value using trapezium area formulae. Based on the comparison between both control techniques, it is found that the line following surveillance robot with fuzzy logic controller works faster than conventional switching method to complete the same task with the average oscillation length using the fuzzy logic controller is reduced to half.
Keywords: Fuzzy logic controller, line following robot; oscillation length.
Scope of the Article: Fuzzy Logic.