Design of Testing Environment for Line-Follower Robot with Obstacles 🔗Abstract: To solve shortest path problem using Q-Learning, one testing method is needed. The testing method is showing Q-Learning result using robot and arena with obstacles. This article will explain obstacles and challenges related to the robot kinematics and arena design to fulfill those needs. To be specific, the robot is needed to move in particular manner in testing ground so the test can be conducted properly and the result can be visualized.

Control System for Mobile Robot using FPGA-Based Q-Learning Accelerator 🔗Abstract: Q-Learning algorithm is used in smart navigation, path planning and others. The output of the Q-Learning cannot be directly used to drive motors or control robot to specific function in the testing area. To convert Q-Learning action into low level signal, we need a controller that organize the task of the sensors, the actuators and the main accelerator. In this paper, we present the control system for a mobile robot that uses FPGA-Based Q-Learning Accelerator.

ABSTRACT 🔗Design and Implementation of Communication System of Mobile Robot and FPGA for Smart Navigation Problem 🔗By 🔗Mohamad Imam Firdaus 🔗NIM: 13218025 🔗(Undergraduate Program in Electrical Engineering) 🔗Q-Learning is one of the commonly used Reinforcement Learning methods. To accelerate the performance of Q-Learning, a Q-Learning acceleration hardware based on System on Chip was created. The system is implemented on the FPGA development board PYNQ-Z1. To carry out the testing and implementation process in real cases, a Mobile Robot is made that can be integrated with the FPGA development board.