A study of neural network based inverse kinematics solution for a three-joint robot


Köker R., Öz C., Çakar T., Ekiz H.

Robotics and Autonomous Systems, cilt.49, sa.3-4, ss.227-234, 2004 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 49 Sayı: 3-4
  • Basım Tarihi: 2004
  • Doi Numarası: 10.1016/j.robot.2004.09.010
  • Dergi Adı: Robotics and Autonomous Systems
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.227-234
  • Anahtar Kelimeler: Artificial neural networks, Inverse kinematics solution, Robotics
  • İstanbul Gelişim Üniversitesi Adresli: Hayır

Özet

A neural network based inverse kinematics solution of a robotic manipulator is presented in this paper. Inverse kinematics problem is generally more complex for robotic manipulators. Many traditional solutions such as geometric, iterative and algebraic are inadequate if the joint structure of the manipulator is more complex. In this study, a three-joint robotic manipulator simulation software, developed in our previous studies, is used. Firstly, we have generated many initial and final points in the work volume of the robotic manipulator by using cubic trajectory planning. Then, all of the angles according to the real-world coordinates (x, y, z) are recorded in a file named as training set of neural network. Lastly, we have used a designed neural network to solve the inverse kinematics problem. The designed neural network has given the correct angles according to the given (x, y, z) cartesian coordinates. The online working feature of neural network makes it very successful and popular in this solution. © 2004 Elsevier B.V. All rights reserved.