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Network Delay Forecast and Master-Slave Consistency Enhancement for Remote Surgical Robots
Summary
Network delay in remote surgery can be predicted using a novel forecasting method. This approach enhances master-slave motion consistency and surgical safety by providing real-time delay forecasts.
Area of Science:
- Robotics
- Network Engineering
- Surgical Technology
Background:
- Network delay poses significant risks to remote surgery, impacting motion consistency and patient safety.
- Sudden network delay fluctuations can compromise the integrity of telesurgical procedures.
Purpose of the Study:
- To develop a real-time network delay forecasting method for remote surgery.
- To improve master-slave motion consistency and enhance safety in telesurgery.
Main Methods:
- Real-time calibration of unidirectional network delays.
- Forecasting network delay using a real-time trained parallel recurrent neural network for safety warnings.
- Real-time slave manipulator position forecasting to improve master-slave motion consistency.
Main Results:
- The forecasting method operates effectively on standard computers over distances up to 630 km.
- The method meets real-time requirements and exhibits strong generalization capabilities.
- The impact of network delay on master-slave motion consistency was reduced by 20%-80%.
Conclusions:
- The proposed method enables real-time network delay forecasting for remote surgeries.
- This approach effectively mitigates the impact of network delay on master-slave motion consistency, improving surgical safety.
