In this paper, a MIMO simulated annealing (SA)-based Q-learning method is proposed to control a line follower robot. The conventional controller for these types of robots is the proportional (P) controller. Considering the unknown mechanical characteristics of the robot and uncertainties such as friction and slippery surfaces, system modeling and controller designing can be extremely challenging. The mathematical modeling for the robot is presented in this paper, and a simulator is designed based on this model. The basic Q-learning methods are based pure exploitation and the ε -greedy methods, which help exploration, can harm the controller performance after learning completion by exploring nonoptimal actions. The simulated annealing–based Q-learning method tackles this drawback by decreasing the exploration rate when the learning increases. The simulation and experimental results are provided to evaluate the effectiveness of the proposed controller.

Meeting Name

10th Annual Computing and Communication Workshop and Conference, CCWC (2020: Jan. 6-8, Las Vegas, NV)


Electrical and Computer Engineering

Research Center/Lab(s)

Center for High Performance Computing Research

Keywords and Phrases

Line Follower; Q-Learning; Reinforcement Learning; Robotics; Simulated Annealing

International Standard Book Number (ISBN)


Document Type

Article - Conference proceedings

Document Version

Accepted Manuscript

File Type





© 2020 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

08 Jan 2020