@article{scholars10819,
       publisher = {Science and Information Organization},
         journal = {International Journal of Advanced Computer Science and Applications},
           pages = {207--217},
            year = {2018},
           title = {Continuous path planning of Kinematically redundant manipulator using Particle Swarm Optimization},
            note = {cited By 7},
          volume = {9},
          number = {3},
             doi = {10.14569/IJACSA.2018.090330},
        abstract = {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. {\^A}{\copyright} 2015 The Science and Information (SAI) Organization Limited.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049533943&doi=10.14569\%2fIJACSA.2018.090330&partnerID=40&md5=56aad429c10c816f9dff228a5feca322},
            issn = {2158107X},
          author = {Machmudah, A. and Parman, S. and Baharom, M. B.}
}