relation: https://khub.utp.edu.my/scholars/10819/
title: Continuous path planning of Kinematically redundant manipulator using Particle Swarm Optimization
creator: Machmudah, A.
creator: Parman, S.
creator: Baharom, M.B.
description: 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.
publisher: Science and Information Organization
date: 2018
type: Article
type: PeerReviewed
identifier:   Machmudah, A. and Parman, S. and Baharom, M.B.  (2018) Continuous path planning of Kinematically redundant manipulator using Particle Swarm Optimization.  International Journal of Advanced Computer Science and Applications, 9 (3).  pp. 207-217.  ISSN 2158107X     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049533943&doi=10.14569%2fIJACSA.2018.090330&partnerID=40&md5=56aad429c10c816f9dff228a5feca322
relation: 10.14569/IJACSA.2018.090330
identifier: 10.14569/IJACSA.2018.090330