Motion and Trajectory Constraints Control Modeling for Flexible Surgical Robotic Systems

Abstract

Success of the da Vinci surgical robot in the last decade has motivated the development of flexible access robots to assist clinical experts during single-port interventions of core intrabody organs. Prototypes of flexible robots have been proposed to enhance surgical tasks, such as suturing, tumor resection, and radiosurgery in human abdominal areas; nonetheless, precise constraint control models are still needed for flexible pathway navigation. In this paper, the design of a flexible snake-like robot is presented, along with the constraints model that was proposed for kinematics and dynamics control, motion trajectory planning, and obstacle avoidance during motion. Simulation of the robot and implementation of the proposed control models were done in Matlab. Several points on different circular paths were used for evaluation, and the results obtained show the model had a mean kinematic error of 0.37 ± 0.36 mm with very fast kinematics and dynamics resolution times. Furthermore, the robot's movement was geometrically and parametrically continuous for three different trajectory cases on a circular pathway. In addition, procedures for dynamic constraint and obstacle collision detection were also proposed and validated. In the latter, a collision-avoidance scheme was kept optimal by keeping a safe distance between the robot's links and obstacles in the workspace. Analyses of the results showed the control system was optimal in determining the necessary joint angles to reach a given target point, and motion profiles with a smooth trajectory was guaranteed, while collision with obstacles were detected a priori and avoided in close to real-time. Furthermore, the complexity and computational effort of the algorithmic models were negligibly small. Thus, the model can be used to enhance the real-time control of flexible robotic systems.

Trajectory Planning of Robot Manipulator Based on RBF Neural Network

“…(2) The study designs a new adaptive robust controller based on an RBF neural network, which uses the strong robustness of adaptive control theory and the self-learning and nonlinear characteristics of RBF neural networks to deal with the nonlinearity and uncertainty of high DOF manipulators. (3) The study designs and builds an experimental platform for the trajectory planning of manipulators and carries out the actual trajectory planning experiments based on this experimental platform, which verifies the effectiveness and feasibility of the proposed method.…”

“…A robot manipulator is a nonlinear and uncertain system. Manipulator trajectory planning should not only consider obstacle avoidance, trajectory accuracy, smooth operation, energy consumption, among other factors, but also needs to consider the problems of external interference, communication delay, and the nonlinearity and uncertainty of robot manipulators [ 2 , 3 , 4 , 5 ]. In order to solve these problems, many researchers have studied the kinematics formula, dynamic model, and control technology of robot manipulators.…”

Research progress and development trend of surgical robot and surgical instrument arm

“…For the future operation of surgical robots, the trajectory workspace and preoperative path planning of surgical instrument arms should be paid attention to. 101 Surgical robots used in clinical applications must develop a set of efficient workspace analysis and path planning schemes before surgery. Surgical stereotyping is the key to preoperative planning, and preoperative target positioning accuracy, preoperative image and spatial mapping should be considered.…”

Space Detumbling Robot Arm Deployment Path Planning Based on Bi-FMT* Algorithm

“…Now, the solution for handling uncertainty is mainly divided into three categories. One is to optimize the design of a new spatial structure, as in [ 31 , 32 ]; another is to change the way of thinking and decompose the problem reasonably and abstractly, as explored by Kumar et al, where they decomposed any 3D motion into a 3D translation and three rotations about specific axes related to the object, which allows planning for 3D dexterous in-hand manipulation with a moderate increase in complexity in just a few seconds [ 33 ]; the third is to use probabilistic analysis methods. Sampling-based path planning achieves an optimal solution under probability analysis through a reduction in constraints and backward detection and evaluation, which can not only ensure the calculation efficiency but also deal with various constraints well.…”