Trajectory planning in parallel kinematic manipulators using a constrained multi-objective evolutionary algorithm

Chun Ta Chen, Hoang Vuong Pham

Research output: Contribution to journalArticle

30 Citations (Scopus)


Generating manipulator trajectories considering multiple objectives with kinematics and dynamics constraints is a non-trivial optimization. In this paper, a constrained multi-objective genetic algorithm (MOGA) based technique is proposed to address this problem for a general motor-driven parallel kinematic manipulator. The planning process is composed of searching for a motion ensuring the accomplishment of the assigned task, minimizing the traverse time, and expended energy subject to various constraints imposed by the associated kinematics and dynamics of the manipulator. This problem is treated via an adequate parametric path representation in the task space of the moving platform, and then the use of the constrained MOGA for solving the resulted nonlinear multi-objective optimization problem. Simulation results are presented for the trajectories of the parallel kinematic manipulator, and a subsequent comparison with the weighted sum method is also carried out.

Original languageEnglish
Pages (from-to)1669-1681
Number of pages13
JournalNonlinear Dynamics
Issue number2
Publication statusPublished - 2012 Jan 1



  • MOGA
  • Multi-objective optimization
  • Parallel kinematic manipulator
  • Pareto front
  • Trajectory planning

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Aerospace Engineering
  • Ocean Engineering
  • Mechanical Engineering
  • Applied Mathematics
  • Electrical and Electronic Engineering

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