PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Trajectory Optimization of a SCARA Manipulator Using Particle Swarm Optimization

Autorzy
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The work presents the use of one of the heuristic algorithms - the Particle Swarm Optimization method - to determine the optimal trajectory of end-effector of a SCARA manipulator. The task was to calculate the shortest path connecting two defined points avoiding obstacles. It is assumed that the transfer of elements above obstacles is impossible, therefore the problem is considered in two-dimensional space. The influence of the number of points creating the trajectory, the number of iterations, the impact of cognitive and social parameters as well as the inertia weight on the action of the algorithm and the study results has been analyzed. The shortest trajectory, the position of the arms (using the inverse kinematics), the angular velocity and angular acceleration (using the backward difference method) for each arm have been determined.
Rocznik
Strony
45--52
Opis fizyczny
Bibliogr. 21 poz., rys., wykr., tab.
Twórcy
autor
  • Czestochowa University of Technology, Faculty of Mechanical Engineering and Computer Science
autor
  • Czestochowa University of Technology, Faculty of Mechanical Engineering and Computer Science
Bibliografia
  • 1. Awrejcewicz, J. (2012). Classical Mechanics: Kinematics and Statics. Springer, New York.
  • 2. Bai, Q. (2010). Analysis of particle swarm optimization algorithm. Computer and Information Science, 3(1):180–184.
  • 3. Buratowski, T. (2012). Teoria robotyki. Wydawnictwo AGH, Kraków.
  • 4. Cekus, D., Skalik, A., Skrobek, D., and Waryś, P. (2015). Kinematic analysis of four degrees of freedom manipulator. Solid State Phenomena, Mechatronic Systems and Materials VI:277–282.
  • 5. Cekus, D. and Waryś, P. (2015). Identification of parameters of discrete-continuous models. AIP Conf. Proc. 1648, 850055 (2015).
  • 6. Cheng, R. and Yao, M. (2001). Particle swarm optimizer with time-varying parameters based on a novel operator. Applied Mathematics & Information Sciences, 5(2):33–38.
  • 7. Clerc, M. and Kennedy, J. (2002). The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE transactions on Evolutionary Computation, 6(1):58–73.
  • 8. Deb, K. (2001). Multi-objective optimization using evolutionary algorithms. John Wiley & Sons.
  • 9. Dorigo, M. and Stützle, T. (2004). Ant colony optimization: overview and recent advances. MIT Press.
  • 10. Gonet, M. (2011). Excel: w obliczeniach naukowych i inżynierskich. Helion.
  • 11. Henrici, P. (1962). Discrete variable methods in ordinary differential equations.
  • 12. Holland, J. H. (1975). Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor.
  • 13. Kennedy, J. (1995). Particle swarm optimization. Proceedings of the IEEE International Conference on Neutral Networks, 4:1942–1948.
  • 14. Kirkpatrick, S., Gelatt, C., and Vecchi, M. (1983). Optimization by simulated annealing. Science, 220(4598):671–680.
  • 15. Mori, H. (1999). Recent trends of meta-heuristics applications in power systems. In Conference Proceedings. 1999 IEEE International Conference on, volume 6, pages 493–496. IEEE.
  • 16. Panda, S., Mishra, D., and Biswal, B. B. (2013). Revolute manipulator workspace optimization: A comparative study. Applied Soft Computing, 13(2):899–910.
  • 17. Rygałło, A. (2008). Robotyka dla mechatroników, Podręcznik w postaci elektronicznej dla studetów kierunku Mechatronika. Politechnika Częstochowska "Plan Rozwoju Politechniki Czestochoskiej".
  • 18. Saramago, S. and Steffen, V. (1998). Optimization of the trajectory planning of robot manipulators taking into account the dynamics of the system. Mechanism and machine theory, 33(7):883–894.
  • 19. Siciliano, B., Sciavicco, L., Villani, L., and Oriolo, G. (2009). Robotics: modelling, planning and cotrol. Springer-Verlag, London.
  • 20. Szczepanik, M. (2013). Algorytmy rojowe w optymalizacji układów mechanicznych. Wydawnictwo Politechniki Gliwickiej, Gliwice.
  • 21. Tarnowski, W. (2011). Optymalizacja i polioptymalizacja w technice. Wydawnictwo Uczelniane Politechniki Koszalinskiej, Koszalin.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d6548ee6-4f1a-45ba-857e-03ca38a78f0c
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.