Continuous path planning of Kinematically redundant manipulator using Particle Swarm Optimization

Affiani Machmudah, Setyamartana Parman, M. B. Baharom

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)207-217
Number of pages11
JournalInternational Journal of Advanced Computer Science and Applications
Issue number3
Publication statusPublished - 2018
Externally publishedYes


  • Genetic algorithm
  • Grey wolf optimizer insert
  • Particle swarm optimization
  • Path planning
  • Redundant manipulator


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