Research On System Design And Control Method Of Transoral Surgical Robot

The mouth,head and neck are important areas for maintaining the functions of human breathing,speech,chewing and appearance,but they are also areas with high incidence of tumors.According to statistics from the Health and Family Planning Commission in 2017,oral tumors rank among the top ten in the incidence of systemic tumors.Traditional oropharyngeal cancer surgery requires cutting the trachea and increasing the gastroesophagus.Adding adjuvant chemotherapy technology will not only severely delay postoperative recovery,but may also risk postoperative wound infection,scarring and adhesions.In recent years,with the development of robotics,imaging and endoscopy,medical robots represented by Da Vinci have been widely used in minimally invasive abdominal surgery.Surgical robots for narrow cavities such as the oral cavity need further research.The optimized design and precise control of surgical robots for the oral approach have become the international frontier research hotspot.In this paper,a new type of rigid-flexible coupling surgical robot is designed for the minimally invasive surgery of the narrow cavity through the oral approach,and focuses on the optimization design of the robot's body structure and the precise control of the continuum robot.The surgical robot adopts a linear drive mode and has three joints: shoulder,elbow and wrist.The shoulder and elbow joints are a pair of identical gear articulated joints,which can be combined to provide the robot with lateral translational motion.This is the basic ability for the robot to perform surgery after entering the cavity.The wrist joint adopts a continuum structure,which has the characteristics of a super-redundant manipulator,and has the flexibility and flexibility required for surgery,but it also has the problems of low motion accuracy and poor load capacity.For the motion control of the robot,this article first adopts the traditional constant curvature assumption to derive the forward and inverse kinematics of the robot,and uses simulation to verify the robot's ability to complete the surgical target task.After that,focus on the motion control of the continuum robot.Under no-load conditions,the offline neural network method is used to compensate for its inherent friction,hysteresis,backlash and other nonlinear errors.In the case of variable load,an adaptive method is proposed.The hybrid neural network PID control algorithm.In order to verify the correctness of the proposed control method,an experimental platform was built,and the NDI optical tracking equipment was used to detect the position of the end of the continuum,so that the algorithm formed a closed loop.A spring force-position coupling test platform was made to simulate the complex variable load scene during the operation.The interactive experiment between the continuum robot and the test platform verified the accuracy and robustness of the proposed motion control algorithm.