%0 Journal Article
%@ 2158107X
%A Machmudah, A.
%A Parman, S.
%A Baharom, M.B.
%D 2018
%F scholars:10819
%I Science and Information Organization
%J International Journal of Advanced Computer Science and Applications
%N 3
%P 207-217
%R 10.14569/IJACSA.2018.090330
%T Continuous path planning of Kinematically redundant manipulator using Particle Swarm Optimization
%U https://khub.utp.edu.my/scholars/10819/
%V 9
%X This paper addresses a problem of a continuous path planning of a redundant manipulator where an end-effector needs to follow a desired path. Based on a geometrical analysis, feasible postures of a self-motion are mapped into an interval so that there will be an angle domain boundary and a redundancy resolution to track the desired path lies within this boundary. To choose a best solution among many possible solutions, meta-heuristic optimizations, namely, a Genetic Algorithm (GA), a Particle Swarm Optimization (PSO), and a Grey Wolf Optimizer (GWO) will be employed with an optimization objective to minimize a joint angle travelling distance. To achieve n-connectivity of sampling points, the angle domain trajectories are modelled using a sinusoidal function generated inside the angle domain boundary. A complex geometrical path obtained from Bezier and algebraic curves are used as the traced path that should be followed by a 3-Degree of Freedom (DOF) arm robot manipulator and a hyper-redundant manipulator. The path from the PSO yields better results than that of the GA and GWO. © 2015 The Science and Information (SAI) Organization Limited.
%Z cited By 7