Mu Lin

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About

Mu Lin’s research stands at the intersection of robotics, virtual reality, and artificial intelligence, with a focused drive to make robotic systems more intelligent and accessible through immersive simulation. His most influential work, “Research on robot arm control based on Unity3D machine learning” (49 citations), pioneers the use of deep reinforcement learning within the Unity3D engine to train robotic arms. By designing sophisticated reward functions, Lin enables robots to learn precise, adaptive movements autonomously—a breakthrough that bridges the gap between virtual training environments and real-world robotic dexterity. Complementing this, his paper “Construction of Robotic Virtual Laboratory System Based on Unity3D” (21 citations) translates cutting-edge research into practical education. Here, Lin develops a fully immersive virtual simulation teaching system, using the robotic arm as a central model to train students in a risk-free, interactive digital lab. This work has been directly applied in PC-based teaching platforms, democratizing access to advanced robotics training. Collectively, Lin’s contributions demonstrate how game-engine technology can revolutionize both machine learning for control systems and hands-on engineering education, making complex robotics more intuitive to teach and faster to deploy.