Indonesian Journal of Electrical Engineering and Computer Science Vol. 20, No. 1, October 2020, pp. 552~562 ISSN: 2502-4752, DOI: 10.11591/ijeecs.v20.i1.pp552-562  552 Journal homepage: http://ijeecs.iaescore.com A review of controller approach for autonomous guided vehicle system Faiza Gul 1 , Syed Sahal Nazli Alhady 2 , Wan Rahiman 3 1,2,3 School of Electrical and Electronic Engineering, Universiti Sains Malaysia (USM), Malaysia 3 Cluster of Smart Port and Logistics Technology (COSPALT), Universiti Sains Malaysia, Malaysia Article Info ABSTRACT Article history: Received Feb 4, 2020 Revised Apr 6, 2020 Accepted Apr 20, 2020 The autonomous guided vehicle is a great and important platform for control systems. Their non-linear nature helps in analysing the control algorithms more efficiently and effectively. The main purpose of path planning is to find the optimal path avoiding the time complexity so environment can be modeled completely. For path planning numerous algorithms have been proposed to solve their non-linear nature. The paper contains brief explanation on AGV application, and its controller design architecture have been discussed with advantages and disadvantages, e.g. Fuzzy control, Neural Control, Back-stepping control, Adaptive control, Sliding mode control and PID control and linear quadratic regulator. At last a brief conclusion has been drawn on the bases of strength and weakness of all algorithms. The research will help the readers to understand mobile robotic path planning with different controllers. Keywords: Autonomous guided vehicle Control system techniques Copyright © 2020 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Wan Rahiman, School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Nibong Tebal, 14300, Penang Malaysia. Email: wanrahiman@usm.my 1. INTRODUCTION The automated guided vehicle can be upgraded into autonomously controlled, famously known as autonomous guided vehicle (AGV), is used in industrial applications to transfer materials from pickup place to drop off place. It is the only kind of transportation, which follows guidance to reach destination. Material handling systems uses AGV, which are used in facilities such as distribution centers, manufacturing plants, terminals and warehouses. Their performance effects the whole delivery system. Wheel based or computer based are their controlling parameters. Their motion is dependent on the combination of sensor-based guidance and software- based guidance systems. They have a predictable path for their movement which also includes obstacle avoidance and detection. They include transportation of goods and raw material inside the vicinity of industry or warehouses avoiding the obstacle and ensuring the safe delivery at destination point. Material handling by the help of AGV has also gained importance in facilities such has warehouse, manufacturing plant, distribution terminals and centers. In terms of algorithm design, autonomous navigation is using control structure architecture based on automated guided system. Then the issues related to these facilities using AGV can be divided into; estimated number of vehicles, guide path, idle-positioning, and vehicle scheduling and battery management. Bio-inspired techniques are most popular, and researchers are implementing them solving path planning problem for AGV or mobile robots [1]. The popular bio-inspired algorithms are based on the living creature behavior which include birds, bees, ants, whale, bat, fish, wolf [2-8]. Randomly exploring tree algorithm with pure pursuit controller can be found in [9]. Examples can be found in, robotics, physics, and control engineering and rehabilitation science [10]. The paper describes the review related to AGV. There are records of considerable number of researches that describe addressing path planning and obstacle avoidance problem using algorithms [11-13].