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
2011-12-01
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Genetic algorithms , Inverse kinematics , Optimal trajectory , Robotic manipulator , Angular displacement , Computing cost , Inverse kinematics problem , Multi-objective functions , Optimal trajectories , Planar robotic manipulator , Positioning error , Robotic manipulators , Computer simulation , Flexible manipulators , Intelligent robots , Intelligent systems , Inverse problems , Knowledge engineering , Optimization , Robotics , Trajectories
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