Dynamic analysis with optimum trajectory planning of multiple degree-of-freedom surgical micro-robot

• Main Authors: Khaled Mohamed, Hassan Elgamal, Amr Elsharkawy
• Format: Article
• Language: English
• Published: Elsevier 2018-12-01
• Series: Alexandria Engineering Journal
• Online Access: http://www.sciencedirect.com/science/article/pii/S1110016818302047

The present work aims to analyze kinematics and dynamics accompanied with an optimum trajectory planning, of a multiple degree-of-freedom positioning surgical micro-robot. The kinematic model was developed using Denavit–Hartenberg algorithm, while dynamic model was developed using Lagrange technique. The trajectory optimization was implemented using different local, global and hybrid optimization techniques. For local optimization, “Fmincon” was employed. Genetic Algorithm (GA), Pattern Search (PS), and Particle Swarm (PSO) were utilized as global optimization techniques. In hybrid optimization approach, GA was used for global optimization while PS was utilized as a local optimization technique for further results refinement. Polynomials of sixth order and fourth order were assumed during all trajectory optimization approaches. The objective function was assumed to minimize the total consumed energy by the positioning manipulator. Non-optimized analysis was investigated as well, using several conventional trajectory planning techniques including fifth order polynomial, third order polynomial, cycloidal formula and elliptical formula. The angle of rotation for all joints ranged from zero to one and half radian, and the motion duration was five seconds for all the presented results. MATLAB codes were created for simulation and optimization processes. Keywords: Micro-robot, Optimal trajectory, Dynamic analysis, Kinematic analysis, Genetic algorithm, Particle swarm, Pattern search, Hybrid optimization