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

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 ki...

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Vydáno v:Nonlinear dynamics Ročník 67; číslo 2; s. 1669 - 1681
Hlavní autoři: Chen, Chun-Ta, Pham, Hoang-Vuong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Dordrecht Springer Netherlands 01.01.2012
Springer Nature B.V
Témata:
Automotive Engineering
Classical Mechanics
Computer simulation
Constraints
Control
Dynamical Systems
Engineering
Evolutionary algorithms
Genetic algorithms
Kinematics
Manipulators
Mechanical Engineering
Multiple objective analysis
Nonlinear dynamics
Optimization
Original Paper
Searching
Task space
Trajectories
Trajectory planning
Vibration
MOGA
Pareto front
Parallel kinematic manipulator
Multi-objective optimization
Trajectory planning
ISSN:0924-090X, 1573-269X
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Popis
Shrnutí: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.
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ISSN:0924-090X
1573-269X
DOI:10.1007/s11071-011-0095-2