Research Progress of Collaborative Robot Arm Control Strategy Optimization Based on Digital Twin

With the application expansion of collaborative robot arm across multiple fields, its safety and control issues in complex environments have become increasingly prominent. Digital twin technology provides a solution to this problem. This paper focuses on the research progress of collaborative robot arm control strategy optimization driven by digital twin technology in recent years. The definition, model and key technologies of digital twin are elaborated first. Then a review is conducted from four dimensions: virtual preview and predictive control, reinforcement learning training and transfer, “virtual-to-physical control” closed-loop architecture and low-latency communication, and human-robot collaborative control. Finally, its future development trends are pointed out and the core challenges that it faces are analyzed, which provides a direction for technical research and application so as to contribute to the development of safe and efficient human-robot collaborative systems.