A direct approach to solving trajectory planning problems using genetic algorithms with dynamics considerations in complex environments Articles uri icon

authors

  • ABU-DAKKA, FARES JAWAD MOH D
  • VALERO, FRANCISCO J.
  • Suñer, Jose Luis
  • Mata Amela, Vicente

publication date

  • March 2015

start page

  • 669

end page

  • 683

issue

  • 3

volume

  • 33

international standard serial number (ISSN)

  • 0263-5747

electronic international standard serial number (EISSN)

  • 1469-8668

abstract

  • This paper presents a new genetic algorithm methodology to solve the trajectory planning problem. This methodology can obtain smooth trajectories for industrial robots in complex environments using a direct method. The algorithm simultaneously creates a collision-free trajectory between initial and final configurations as the robot moves. The presented method deals with the uncertainties associated with the unknown kinematic properties of intermediate via points since they are generated as the algorithm evolves looking for the solution. Additionally, the objective of this algorithm is to minimize the trajectory time, which guides the robot motion. The method has been applied successfully to the PUMA 560 robotic system. Four operational parameters (execution time, computational time, end-effector distance traveled, and significant points distance traveled) have been computed to study and analyze the algorithm efficiency. The experimental results show that the proposed optimization algorithm for the trajectory planning problem of an industrial robot is feasible.

keywords

  • Robotics
    Trajectory planning
    Obstacles avoidance
    Genetic algorithms