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  • 标题:Continuous Path Planning of Kinematically Redundant Manipulator using Particle Swarm Optimization
  • 作者:Affiani Machmudah ; Setyamartana Parman ; M.B. Baharom
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2018
  • 卷号:9
  • 期号:3
  • DOI:10.14569/IJACSA.2018.090330
  • 出版社:Science and Information Society (SAI)
  • 摘要: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.
  • 关键词:Path planning; redundant manipulator; genetic algorithm; particle swarm optimization; grey wolf optimizer insert
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