<

This Article Statistics
Viewed : 23 Downloaded : 17


 

Double Robot Arm Movement Planning Using Genetic Algorithm

Metin Sevinçli, Ersin Özdemir

Abstract

In this study, it is aimed to ensure that the robot arms on both sides of the conveyor belt reach the targets on the conveyor belt in equal or close numbers. In the system, a band that can carry 1025 materials per unit time is used. Each frame to be processed on the conveyor belt is considered a matrix of 25 rows and 41 columns. It is aimed that the robots make a division of labor for a common problem and that the number of materials they collect and the path they cover are equal or close. For this purpose, optimization of the system has been provided by using Genetic Algorithm technique. With the developed algorithm, the work sharing between the robots in terms of the number of materials received and the total distance traveled has been achieved as close to 100%.

Keywords

Robot, Optimization, Genetic Algorithms.

Volume 4, No 3, SUPPLEMENT I of SYMPOSIUM ARTICLES, pp 77-83, 2019



Download full text   |   How to Cite   |   Download XML Files

References
  • Aksungur S. and Kavlak K. (2009). Scara robotun engelli ortamda çarpışmasız hareketinin yapay sinir ağları ve genetik algoritma kullanılarak gerçekleştirilmesi. Selçuk Üniversitesi Teknik Bilimler Meslek Yüksekokulu Teknik-Online Dergi, 8(2), 112-126.
  • Al-Jazarí, Encyclopædia Britannica Ultimate Ref. Suite. Chicago: Encyclopædia Britannica, 2011.
  • Arif M. and Haider S. (2017). An Evolutionary Traveling Salesman Approach for Multi-Robot Task Allocation. DOI: 10.5220/0006197305670574 In Proceedings of the 9th International Conference on Agents and Artificial Intelligence (ICAART 2017), 567-574 ISBN: 978-989-758-220-2
  • Güllü A. (2017). Labirentlerde yapay zekâ tabanlı yön bulma algoritmaları kullanan bir gezgin robot geliştirilmesi. Doktora tezi, Trakya Üniversitesi, Fen Bilimleri Enstitüsü.
  • Kert M., (2006). Gerçek görüntüden elde edilen koordinatlarla robot kol hareket optimizasyonu. Mustafa Kemal Üni. FBE.Yüksek Lisans Tezi.
  • Lamini C, Benhlima S, Elbekri A. (2018). Genetic Algorithm Based Approach for Autonomous Mobile Robot Path Planning. Procedia Computer Science, Volume 127, 180-189, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2018.01.113).
  • Ma, X., Zhang, Q., & Li, Y. (2007). Genetic Algorithm-based Multi-robot Cooperative Exploration. 2007 IEEE International Conference on Control and Automation, 1018-1023.