Robotic Arm Manipulation : Digital Twin Pick-and-Place

Abstract

Modern industries increasingly rely on robotic systems to improve operational efficiency and to reduce human labour, time, and cost in areas such as logistics, manufacturing, and material handling. This thesis focuses on the application of robotic manipulation using a six-axis articulated robotic arm implemented as a digital twin. The selected platform is the digital twin of the entry-level Niryo Ned2 robot, which is operated within the Gazebo simulation environment. The study aims to examine how the digital twin of the Niryo Ned2 can serve as a practical tool for implementing and observing a basic pick-and-place operation using Python-based control commands. The research investigates whether a simple joint-space control approach is sufficient to achieve reliable pick-and-place execution in a simulated environment. The work was carried out using the Ubuntu operating system, the Robot Operating System (ROS), and the Gazebo simulator. A Python-based control script was developed to command the robot’s joints and gripper, defining a sequence of movements for three consecutive pick-and-place operations. The digital twin environment enabled safe testing and observation of the robot’s behaviour before any real-robot implementation. The results show that the Niryo Ned2 digital twin successfully executed the programmed pick-and-place tasks in the Gazebo simulator, with the robot consistently completing the defined motion sequences across multiple executions. Minor limitations were observed in terms of object placement accuracy and gripper behaviour, particularly when objects were placed in proximity. Overall, the study demonstrates that a simple Python-based joint-space control approach can effectively support basic robotic manipulation tasks in a digital twin environment and highlights the value of digital twins as accessible tools for robotic programming, experimentation, and education.