This paper presents the generation of optimal trajectories by genetic algorithms (GA) for a planar robotic manipulator. The implemented GA considers a multi-objective function that minimizes the end-effector positioning error together with the joints angular displacement and it solves the inverse kinematics problem for the trajectory. Computer simulations results are presented to illustrate this implementation and show the efficiency of the used methodology producing soft trajectories with low computing cost. © 2011 Springer-Verlag Berlin Heidelberg.
Optimal trajectory and solution of the inverse kinematics of a robotic manipulator by genetic algorithms
01.12.2011
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Robotic manipulator , Optimization , Optimal trajectories , Positioning error , Inverse kinematics problem , Multi-objective functions , Inverse kinematics , Computer simulation , Genetic algorithms , Intelligent robots , Knowledge engineering , Computing cost , Angular displacement , Trajectories , Inverse problems , Intelligent systems , Planar robotic manipulator , Robotics , Robotic manipulators , Flexible manipulators , Optimal trajectory
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