In the field of vascular surgery, vascular intervention surgery is an efficient minimally invasive treatment method. However, traditional intervention procedures require doctors to wear lead aprons for an extended period of time, and there is also a risk of radiation exposure. This not only poses health hazards for the medical professionals but also has the potential to adversely affect surgical efficiency. With the development and application of endovascular interventional robotics (EIR), it is possible to reduce doctor's radiation exposure while providing higher operational precision and stability over traditional methods. Two key technologies, automatic instrument recognition and real-time tracking, enable EIR to control and assess the orientation of instruments in complex intervention surgeries, ensuring the quality and safety of treatments. Current research predominantly focuses on using intervention imaging to enable EIR to accurately detect and locate instruments in blood vessels in real-time, essentially allowing the robot to perform surgery based on observed image information. Simultaneously, the collaborative work of instrument recognition technology with EIR have significant potential value. This requires robots not only to execute commands precisely but also to understand and predict the operator's intentions. The development of artificial intelligence technology, is expected to support robots in more accurately identifying and tracking instruments and correcting positioning errors, ultimately achieving true collaborative surgery. Here, the authors analyze the application of the two major technologies, automatic instrument recognition and real-time tracking, in the field of EIR, and comprehensively discuss their prospects for clinical applications, along with of the development of relevant technologies both domestically and abroad.