With the rapid development of intelligent manufacturing technologies, industrial robots have become indispensable equipment in modern manufacturing, and their application range is expanding. To meet the requirements of the new engineering education reform and enhance students' practical abilities and innovative thinking, this study aims to design an industrial robot motion simulation platform based on digital twin technology. The platform helps students understand the kinematics principles, control strategies, and digital twin technology of industrial robots, thereby improving their practical skills and innovation and addressing the gap between theory and practice in traditional teaching.

This platform is based on the desktop industrial robot RoArm-M1, combining kinematic modeling, virtual-physical bidirectional real-time mapping, and human-computer interaction design. Digital twin technology is employed for robot motion simulation. By establishing the kinematic model of RoArm-M1, forward and inverse kinematics algorithms are used to compute the robot's motion trajectory. The simulation considers the robot's movement constraints in different postures to ensure the accuracy and reliability of the motion process. Virtual-physical bidirectional mapping technology is used to establish the mapping relationship between the robot model and the real robot.

The industrial robot motion simulation platform based on digital twin technology successfully achieves real-time synchronization between the virtual and physical robots. Through the platform, students can observe and operate the robot's motion in a virtual environment, deepening their understanding of robot kinematics and control strategies. The platform’s educational modules cover kinematics theory, control strategy simulation, and motion control algorithm debugging, helping students systematically learn and master relevant robot knowledge while strengthening their hands-on practical skills.

The digital twin industrial robot motion simulation platform designed in this study combines virtual-physical mapping, kinematic control, and trajectory planning, offering an innovative teaching tool. It effectively merges theoretical knowledge with practical application, enhancing students' learning experience and understanding of robot motion principles. The platform also promotes the use of digital twin technology in intelligent manufacturing education, contributing to the advancement of engineering education reforms and the improvement of practical teaching quality. In the future, the platform can be optimized to support more complex industrial scenarios and broader educational needs in intelligent manufacturing.