Research On Surgical Robot Motion Planning And Teleoperation Control Strategy Under RCM Constraint

With the development of society and the advancement of medical conditions,surgical robots have gradually become the focus of academic research.The development and application of surgical robots can effectively improve the efficiency and accuracy of surgical operations,reduce the difficulty of surgical operations,and accelerate the recovery rate of patients after surgery.However,there are still some problems.First of all,for the problem of RCM point constraints,currently mature robot systems all use specially designed mechanical structures to passively ensure RCM point constraints,and their complex configurations lack flexibility.Regarding the RCM point constraint problem of serial robotic arms,although some scholars have proposed various active constraint algorithms,these algorithm models are complex,and some algorithms need to be derived for specific robotic arm models,and their versatility is poor.Therefore,for serial robotic arms RCM point constraint problem currently lacks a mature,reliable and easy-to-use solution.Secondly,the current surgical robot systems mostly use master-slave teleoperation,rarely combined with motion planning assistance technology.When faced with complex or high-precision trajectories,such as knotting and coiling,the efficiency of the operation is low and requires long-term training,so the cost is expensive.In view of the above problems,this paper mainly studies the teleoperation and motion planning strategies of the dual-arm surgical robot under the constraint of RCM point.The final result is to build a dual-arm surgical robot system on the hardware.In algorithm we propose two models of RCM point constraint algorithms with simple and strong applicability.Based on this,the master-slave teleoperation of the dual-arm surgical robot is realized.Develop hand-eye coordination algorithms to improve operational efficiency.Combining the ideas of generative network and dimensionality reduction motion planning,it is applied to the knotting and coiling movement to realize semi-autonomous decision-making and auxiliary execution,which improves the intelligence of the system to some extent.It mainly includes the following aspects:1)Aiming at the problem that the RCM constraint algorithm of the serial manipulator is not mature,two kinds of RCM constraint algorithms are proposed based on geometric derivation method and nonlinear optimization method respectively in this paper,which are applicable to different scenes and effectively solve the problem of RCM constraint of the serial manipulator.2)Aiming at the problem that surgical robotic system has a lot of equipment and the coordinate system,which results in operating direction disorder.We first realize the fast calibration of equipment in surgical robot system.Surgical robot hand-eye coordination algorithm is proposed based on the calibration results,which ensure the simple operation,reduce the learning difficulty and time cost.3)Aiming at the problem of complex robot end trajectory and difficulty in teleoperation,we propose to learn and autonomously generate trajectories based on the generative network,use the dimensionality reduction idea for motion planning based on the results of the generative network.Finally,the time optimal algorithms are used to generate a complete time-stamped trajectory for the planning results,which improves the intelligence of the system to a certain extent.4)Based on the hardware platform built in this paper,the master-slave teleoperation delay,slave-side motion resolution,RCM point constraints and comprehensive experimental tests were carried out.The experimental results show that the dual-arm surgical robot built in this paper and the master-slave teleoperation control strategy and motion planning method developed in this paper have certain effectiveness and practical value.