Confidence-based Intent Prediction for Teleoperation in Bimanual Robotic Suturing

--Robotic-assisted procedures offer enhanced precision, but while fully autonomous systems are limited in task knowledge, difficulties in modeling unstructured environments, and generalisation abilities, fully manual teleoperated systems also face challenges such as delay, stability, and reduced sensory information. T o address these, we developed an interactive control strategy that assists the human operator by predicting their motion plan at both high and low levels. At the high level, a surgeme recognition system is employed through a Transformer-based real-time gesture classification model to dynamically adapt to the operator's actions, while at the low level, a Confidence-based Intention Assimilation Controller adjusts robot actions based on user intent and shared control paradigms. The system is built around a robotic suturing task, supported by sensors that capture the kinematics of the robot and task dynamics. Experiments across users with varying skill levels demonstrated the effectiveness of the proposed approach, showing statistically significant improvements in task completion time and user satisfaction compared to traditional teleoperation. N traditional teleoperation the human operator fully controls the robot's movements [1]. Robots like the da Vinci Surgical System are equipped with sensors and models offering valuable local information inaccessible to the human operator, such as during visual occlusions or operations with different sensory modalities. By spanning across the spectrum between traditional fully manual teleoperation and full autonomy, shared control leverages the benefits of both to enhance teleoperation with the robot's sensory data and control [2]. While demonstrated for suturing assistance [3], [4], these methods overlook the impact on positional uncertainty, environmental unknowns, or instrument errors. For example, robotic surgery cameras are frequently occluded by body tissues or parts of the robot [5].