Continuous Path Planning of Kinematically Redundant Manipulator using Particle Swarm Optimization

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.

Authors and Affiliations

Affiani Machmudah, Setyamartana Parman, M. B. Baharom

Keywords

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  • EP ID EP278260
  • DOI 10.14569/IJACSA.2018.090330
  • Views 74
  • Downloads 0

How To Cite

Affiani Machmudah, Setyamartana Parman, M. B. Baharom (2018). Continuous Path Planning of Kinematically Redundant Manipulator using Particle Swarm Optimization. International Journal of Advanced Computer Science & Applications, 9(3), 207-217. https://europub.co.uk/articles/-A-278260