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.
S. Saadatmand et al., "Autonomous Control of a Line Follower Robot Using a Q-Learning Controller," Proceedings of the 10th Annual Computing and Communication Workshop and Conference (2020, Las Vegas, NV), Institute of Electrical and Electronics Engineers (IEEE), Jan 2020.
The definitive version is available at https://doi.org/10.1109/CCWC47524.2020.9031160
10th Annual Computing and Communication Workshop and Conference, CCWC (2020: Jan. 6-8, Las Vegas, NV)
Electrical and Computer Engineering
Center for High Performance Computing Research
Keywords and Phrases
Line Follower; Q-Learning; Reinforcement Learning; Robotics; Simulated Annealing
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2020 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
08 Jan 2020