AÇIK KAYNAK MEDİKAL YARDIMCI ROBOT KOLUN PYTHON İLE İLERİ KİNEMATİK ANALİZİ

Year 2021, Volume: 9 Issue: 2, 395 - 402, 01.06.2021

Mehmet Gül

https://doi.org/10.36306/konjes.803990

Abstract

Günümüzde Covid-19 gibi pandemik hastalıkların tüm dünyayı hızla etkilemesi ve buna bağlı tüm dünyada yüzbinlerce kişinin hayatına mal olmuşken sağlık çalışanlarının dünya genelindeki özverili çalışmalarının önemi ortaya çıkmıştır. Çalışmada, sağlık çalışanlarının iş yükünün paylaşılması için süreç içerisinde destek elemanları olarak medikal yardımcı makineler üzerine inceleme yapılmıştır. Geliştirilen medikal yardımcı robotik kol, sağlık çalışanlarının iş yükünün paylaşılması açısından özellikle pandemi sürecinde son derece önem arz etmektedir. Geliştirilen robot kol açık kaynak ve de eklemlerinin model baz alınarak uyarlanabilir olması son derece önemli bir özelliktir. Robot kolun açık kaynak olması oluşabilecek telif haklarından kaynaklı sorunlarında giderilmesi açısından son derece önemlidir. Robot kol profesyonel özellikte endüstriyel boyutlarda kullanıma uygun özelliklere sahiptir. Çalışmada kullanılan robot kol 3D yazıcıdan basılmış ve robot kol 5 serbestlik derecesine (5 DoF) sahip mafsallı robot koldur. 3D yazıcıdan basılabilir olması bu tür profesyonel robot kollar açısından maliyet olarak ciddi tasarruf sağlamaktadır. Robot kolun çalışma uzayının belirlenmesi ve ayrıca kontrolü açısından kinematik analiz önemlidir. Bu makalede, çalışma uzayının belirlenmesi, erişebilir noktalarının tespiti için ileri kinematik analizi derin öğrenme ile yapıldı.

Keywords

Açık Kaynak Robot Kol, Python, İleri Kinematik Analiz

Forward Kinematic Analysis of Open Source Medical Assistant Robot Arm with Python

Abstract

Today, pandemic diseases like Covid-19 affect the entire world rapidly, and due to this, the significance of the devoted work of healthcare professionals worldwide has emerged while it has cost the lives of a huge number of individuals around the world. In the study, so as to share workload of healthcare professionals, in the process, medical assistant machines were analyzed as support staff. The developed medical assistant robotic arm is extremely important especially within the pandemic process in terms of sharing burden of healthcare professionals. It is an extremely important feature that the developed robot arm is open source and its joints can be adjusted based on the model. The fact that the robot arm is open source is extremely important in terms of the issues that may emerge from copyrights. The robot arm has features appropriate for use in industrial dimensions with professional features. The robot arm utilized in the study is printed with a 3D printer and also the robot arm is articulated with 5 degrees of freedom (5 DoF). The fact that it can be printed from a 3D printer provides significant cost savings for such professional robot arms. Kinematic analysis is significant regarding determining and controlling the working space of the robot arm. In this study, forward kinematic analysis was done with deep learning for determination of working space and accessible points.

Keywords

Open-Source Robot Arm, Python, Forward Kinematic Analysis

References

• Aspragathos NA, Dimitros JK, 1988. A comparative study of three methods for robot kinematics. IEEE transactions on systems, man, and cybernatics-part B: Cybernatics, vol. 28, no. 2.
• Funda J, Paul RP, 1988. Manipulator kinematics and epsilon algebra, IEEE J. Robot. Automat., vol. 4.
• Kim JH, Kumar VR, 1990. Kinematics of robot manipulator via line transformations, J. Robot. Syst., vol. 7. no. 4, pp. 649-674.
• Maxwell EA, 1900. General homogeneous coordinates in space of three dimensions, Cambridge. U. K.: Cambridge Unv. Press.
• Denavit J, Hartenberg RS, 1955. A kinematic notation for Lower-pair mechanisms based on matrices, ASME Jappl. Mechan. pp. 215-221.
• Ball RS, 1900. The theory of screws, Cambridge. U. K.: Cambridge Unv. Press.
• Liu Y, Wang D, Sun J, Chang L, Ma CX, Ge Y, Gao L. 2015. Geometric approach for inverse kinematics analysis of 6-dof serial robot, IEEE International Conference on Information and Automation, pages 852-855.
• Qiao S, Liao Q, Wei S, Su H, 2010. Inverse kinematic analysis of the general 6R serial manipulators based on double quaternions, Mechanism and Machine Theory 45, 193-199.
• Nubiola A, Bonev IA, 2014. Geometric approach to solving the inverse displacement problem of Calibrated decoupled 6R serial robots, Transactions of the Canadian Society for Mechanical Engineering 38, 31-44.
• Almusawi ARJ, Dülger LC, Kapucu S, 2016. A new artificial neural network approach in solving inverse kinematics of robotic arm (denso vp6242), Computational Intelligence and Neuroscience.
• Köker R, 2013. A genetic algorithm approach to a neural-network-based inverse kinematics solution of robotic manipulators based on error minimization, Information Sciences 222, 528-543.
• Duka AV, 2014. Neural network based inverse kinematics solution for trajectory tracking of a robotic arm, Procedia Technology 12, 20-27.
• Uchiyama M, Iwasawa N, Hakomori K, 1987. Hybrid positon/force control for coordination of two-arm robot. In Proceedings of the IEEE International Conference on Robotics and Automation, pp. 1242–1247.
• Kopf CD, Yabuta T, 1988. Experimental comparison of master/slave and hybrid two arm position/force control, in Proceedings of the IEEE International Conference on Robotics and Automation, vol. 3, pp. 1633–1637.
• Corke PI. 1996. “A robotics toolbox for matlab,” IEEE Robotics Automation Magazine, vol. 3, no. 1, pp. 24–32.
• Kelmar L, Khosla PK. 1990. Automatic generation of forward and inverse kinematics for a reconfigurable modular manipulator system. Journal of Robotic Systems, vol. 7, no. 4, pp. 599–619, 1990. [Online]. Available: http://dx.doi.org/10.1002/rob.462007040.
• Wu Y, Cheng LH, Fan GF, Wang CD, 2014. Inverse kinematics solution and optimization of 6-DOF handling robot. Appl Mech Mater 635–637:1355–1359.
• Github: https://github.com/BCN3D/BCN3D-Moveo (10/06/2020).
• Thingiverse: https://www.thingiverse.com/thing:1693444 (10/06/2020).