2DoF Robotic Arm using Reinforcement Learning

Abstract

The 2DoF Robo-Arm Reinforcement Learning aims to develop an intelligent system that can learn to control a robotic arm with two degrees of freedom using reinforcement learning techniques. The concept here involves the use of a simulated environment in which the robotic arm can interact with different objects and learn to perform tasks such as reaching, grasping, and moving objects. The idea here seeks to improve the efficiency and effectiveness of robotic arm control in industrial and manufacturing applications, enabling them to perform complex tasks with good accuracy and speed. The overview of the proposed system’s objectives, methodology, and results, demonstrating the potential of this technology to control Robotic Arm and also its use in Automation are discussed here