Research On Obstacle Avoidance Path Planning For Minimally Invasive Spine Surgery Robotic Arm

With the development of society and the improvement of technology,patients’ demand for medical technology is constantly increasing.As an advanced technology,the robotic arm has attracted much attention.The use of robotic arms to assist physicians in minimally invasive spine surgery not only improves surgical accuracy and reduces trauma to the patient,but also increases the success rate and reduces the cost of surgery.This is of great importance for domestic medical robotics research.The focus of the research in this paper is on the following main aspects:First of all,combined with the actual surgical environment and requirements of minimally invasive spinal surgery,the robotic arm was selected.The UR5 robotic arm has good motion precision and flexibility,which is very suitable for minimally invasive spinal surgery.This study takes the UR5 robotic arm and solves its kinematics as well as investigates the obstacle avoidance path planning of the algorithm.By establishing a mathematical model based on-parameters,this paper deduces the forward and reverse kinematics formulas of the manipulator,and uses C++ language to write the forward and reverse solution derivation process.In addition,this paper verifies the correctness of the forward and backward solution derivation process using the Robotics Toolbox in MATLAB 2019.Secondly,the problem of collision detection between the robotic arm and the obstacles in the surrounding environment in minimally invasive spine surgery is analyzed.Then,several common collision detection algorithms for enclosing boxes are described in detail,their respective advantages and disadvantages are analyzed,and improvements are made to simplify the modeling of the two themselves according to the dimensional parameters of the robotic arm and the obstacle to be detected.This allows collision detection results to be derived by calculating the spatial distance position between the simplified robot arm and the obstacle model.Then,the algorithm of obstacle avoidance path for minimally invasive spinal manipulator is analyzed and studied.Taking the traditional RRT algorithm as the research,in order to overcome the shortcomings of the traditional RRT algorithm,a new and more efficient RRT algorithm is proposed.Firstly,the artificial potentiometric domain is introduced on the foundation of the traditional RRT algorithm,which makes the directionality of the search enhanced;then the strategy of target biasing is added to improve the efficiency of sampling.These two measures can significantly faster the random tree growth.After the random tree growth,for the problem of unsmoothed paths,firstly,a method of initial path node screening is proposed to make the paths after the search with fewer turns,and secondly,the generated paths are smoothed to make the final paths meet the requirements of the actual motion of the minimally invasive spine surgery robotic arm.Finally,the simulation was carried out in a two-dimensional plane with Visual Studio 2012 and MATLAB2019 b,and the advantages of the improved algorithm were compared.Finally,a simulation model was built in VREP for simulation experiments,and physical verification was also performed on the testbed.Through experimental validation,the effectiveness of the improved RRT algorithm proposed in this paper was successfully demonstrated,and the algorithm was able to plan a collision-free path for the minimally invasive spine surgery robotic arm.