Final Year Project (FYP)Authors: Le, Thi Nhung; Advisor: Nguyen, Dang Khoa (2025)
This paper outlines the design and implementation of a control algorithm for a selfbalancing robot using Deep Reinforcement Learning, specifically the Deep Q-learning algorithm. Self-balancing robots represent a significant search area in robotics, as they require advanced control strategies to maintain stability and adapt to changing environmental conditions. The primary objective of this research is to develop an intelligent system capable of maintaining balance and performing precise maneuvers in response to disturbances and varying circumstances. The Deep Q-learning algorithm enables a robot to learn optimal control policies by interacting with a simulated environment. In this sce... 
