İnsan-robot etkileşiminin biyomimetik yaklaşımla sağlanması

Öz

Bu çalışmada, insan kol ve el hareketlerinin taklit edilmesiyle insan-robot etkileşimini sağlayan biyomimetik bir yaklaşım sunulmuştur. İnsan kol hareketleriyle robotun aynı doğrultuda hareket etmesi sağlanmış ve el hareketleri ile de robot tutucusunun kontrolü sağlanmıştır. Robot hareketi için; ilk olarak insan elinin, bel hizasında orijin noktası olarak belirlenen noktaya olan konumunu verecek kinematik model oluşturulmuştur. Modellemede, insan kolu, ön kol, pazı ve omuz olmak üzere üç ayrı uzuv olarak incelenmiştir. Omuza, pazıya ve ön kola yerleştirilen algılayıcılar ile dönüş açısı bilgileri elde edilmiş ve uzuv uzunlukları ile birlikte matematiksel modelde kullanılmıştır. Bu hesaplamalarda rotasyon kinematiği ve hareket kinematiği matrisleri kullanılmıştır. Tutucu kontrolü için ise bünyesinde EMG sensörleri bulunduran MYO kol bandı kullanılmıştır. Bu kol bandı üzerindeki EMG sensörleri ile kol kaslarından parmak hareketleri algılatılmıştır ve bu hareketler doğrultusunda pnömatik tutucu kontrol edilmiştir.  Uygulamalarda 6-eksen robot kolu kullanılmıştır. Hesaplanan konum verileri ve tutucu bilgisi ethernet üzerinden TCP/IP protokolü ile robot denetleyicisine aktarılmaktadır. Robotun hesaplanan konuma gitmesini ve tutucu kontrolünü sağlayan kod oluşturularak robota aktarılmıştır.  Yapılan testlerde, endüstriyel robotun insan kol ve el hareketleri ile başarılı biçimde kontrol edildiği gözlemlenmiştir.

Anahtar Kelimeler

• Endüstriyel robotlar,Biyomimetik kontrol,Rotasyon ve hareket kinematiği,Tutucu kontrolü,İnsan-robot etkileşimi

Providing the human-robot interaction with biomimetic approach

Öz

In this work, a biomimetic approach to provide human-robot interaction by mimicking the motion of human arm and fingers is presented. The movement of an industrial robot is performed by human arm movement in same direction and the control of gripper is also performed by hand movements. For the movement of robot, as a first step, a kinematic model is obtained to give the position of the human hand to the point determined as the origin point in the waist line. In the modelling, the human arm is considered as three limp that are forearm, biceps and shoulder. The rotational angles are obtained from sensors placed in the shoulder, biceps, and forearm, are used in the mathematical model with limb lengths. Rotation kinematics and kinematics matrices are used in these calculations. For the gripper control, a MYO armband with EMG sensors is used. With this EMG sensor on the armband, finger movements are detected from the arm muscles and the pneumatic gripper was controlled in the direction of these movements. A 6-axis robot arm is used in the applications. The calculated position data and the gripper information are transferred to the robot controller via the TCP/IP protocol over Ethernet. A code that provides reaching of robot to calculated position and control the gripper is created and transferred to robot. In the tests, it has been observed that the industrial robot has been successfully controlled by human arm and hand movements

Anahtar Kelimeler

• Industrial robots,Biomimetic control,Rotation and motion kinematics,Gripper control,Human-robot interaction

Kaynakça

1. Peshkin MA, Colgate JA, Wannasuphoprasit W, Moore C, Gillespie RB, Santos-Munne J, Lorenz A, Akella P. “Cobot architecture”. IEEE Transactions on Robotics and Automation, 17, 377-390, 2001.
2. Colgate JA, Peshkin MA, Wannasuphoprasit W. “Nonholonomic haptic display”. IEEE International Conference on Robotics and Automation, Philadelphia, PA, 23-27 April, 1996.
3. Green SA, Billinghurst M, Chen X, Chase G. “Human‐Robot collaboration: A literature review and augmented reality approach in design”. International Journal of Advanced Robotic Systems. 5(1), 1‐18, 2008.
4. Steinfeld A, Fong T, Kaber D, Lewis M, Scholtz J, Schultz A, Goodrich M. “Common metrics for human-robot interaction”. First ACM SIGCHI/SIGART Conference on Human-robot interaction. Salt Lake City, Utah, USA, March 02 - 03 2006.
5. Groom V, Nass C. “Can robots be teammates?: Benchmarks in human-robot teams”. Interaction Studies, 8(3), 483-500, 2007.
6. Michalos G, Makris S, Papakostas N, Mourtzis D, Chryssolouris G. “Automotive assembly technologies review: challenges and outlook for a flexible and adaptive approach”. CIRP Journal of Manufacturing Science and Technology. 2(2), 81-91, 2010.
7. Krger J, Lien T, Verl A. “Cooperation of human and machines in assembly lines”. CIRPAnnals-Manufacturing Technology, 58(2), 628-646, 2009.
8. Baxter Robot, “How rethink robotics built its new baxter robot worker”. https://spectrum.ieee.org/robotics/industrial-robots/rethink-robotics-baxter-robot-factory-worker (15.04.2019) .

9. Sawyer Robot, “Sawyer: Rethink robotics unveils new robot” https://spectrum.ieee.org/automaton/robotics/industrial-robots/sawyer-rethink-robotics-new-robot (15.04.2019) .
10. Bauzano E, Estebanez B, Garcia-Moralez I. "Collaborative human-robot system for HALS suture procedures".IEEE Systems Journal, 10(3), 957-966, 2014.
11. Ying C, Jia-fan Z, Can-Jun Y, Bin N. “Design and hybrid control of the pneumatic force-feedback systems for Arm-Exoskeleton by using on/off valve”. Mechatronics, 17, 325-335, 2007.
12. Tafazzoli F, Safabakhsh R. “Model-based human gait recognition using leg and arm movements”. Engineering Applications of Artificial Intelligence. 23(8), 1237-1246, 2010.
13. Poppe R. “Vision-based human motion analysis: An overview”. Computer Vision and Image Understanding, 108(2), 4-18, 2007.
14. Jun S, Park J, Park C, Jung IK, Kim YO. “Morphological approach of stereo camera based human motion capture system”. International Conference on Control, Automation and Systems, Seoul Korea, October 17-20 2009.
15. Takeda R, Tadano S, Natorigawa A, Todoh M, Yoshinari S. “Gait posture estimation using wearable acceleration and gyro sensors”. Journal of Biomechanics. 42(15), 86-94, 2009.
16. Zhou, H, Stone T, Hu H, Harris N. “Use of multiple wearable inertial sensors in upper limb motion tracking”. Medical Engineering & Physics. 30(1), 23-33, 2008.
17. Bernmark, E, Wiktorin C. “A triaxial accelerometer for measuring arm movement”. Applied Ergonomics, 33(6), 541-547, 2002.
18. Favre J, Luthi F, Jolles B, Siegrist O, Najafi B, Aminian K. “A new ambulatory system for comparative evaluation of the three-dimensional knee kinematics, applied to anterior cruciate ligament injuries”. Knee Surg sports Traumatol Arthrosc, 14(7), 592-604, 2006.
19. Haid M, Breitenbach J. “Low cost inertial orientation tracking with Kalman fitler”. Applied Mathematics and Computation. 153(2), 567-575, 2004.
20. Kao C, Chen T. “Design and analysis of an orientation estimation system using coplanar gyro-free inertial measurement unit and magnetic sensors”. Sensors and Actuators A: Physical, 144(2), 251-262, 2008.
21. Fourati H, Manamanni N, Afilal L, Handrich Y. “Posture and body acceleration tracking by inertial and magnetic sensing: Application in behavioral analysis of free-ranging animals”. Biomedical Signal Processing and Control, 6(1), 94-104, 2011.
22. Gültekin Y. Bir Endüstriyel Robotun İnsan Kolu Hareketlerinin Ataletsel Ölçümü ile Uzaktan Kontrolü Yüksek Lisans Tezi. TOBB Ekonomi ve Teknoloji Üniversitesi, Ankara, Türkiye, 2012.
23. Kashima T. Hori K. “Control of biomimetic robots based on analysis of human arm trajectories in 3D movements”. Artificial Life Robotics, 21, 24-30, 2016.
24. Ahammed AP, Prabhu KE. “Robotic Arm Control through Human Arm Movement Using Accelerometer” International Journal of Engineering Science and Computing, 6(5), 5639-5641, 2016.
25. Meulen FB, Beijnum BJF, Buurke JH, Peter H. Veltink PH. “Assessment of Lower Arm Movements Using One Inertial Sensor”. 2017 International Conference on Rehabilitation Robotics (ICORR), London, UK, 17-20 July, 2017.
26. Syed A, Agasbal ZT, Melligeri T, Gudur B. “Flex Sensor Based Robotic Arm Controller Using Micro Controller” Journal of Software Engineering and Applications, 5, 364-366, 2012.
27. Lopes J, Simão M, Mendes N, Safeea M, Alfonso J, Neto “Hand/arm gesture segmentation by motion using IMU and EMG sensing”. Procedia Manufacturing, 11, 107-113, 2017.
28. Neto P, Pires N, Moreira AP. “Accelerometer-Based Control of an Industrial Robotic Arm” 18th IEEE International Symposium on Robot and Human Interactive Communication, Toyama, Japan, 27 September-2 October, 2009.
29. Shin S, Tafreshi R, Langari R, “Real-time EMG-Based human machine ınterface using dynamic hand gestures”. 2017 American Control Conference, Seattle, USA, 24-26 May, 2017.
30. Bosch Sesortech. “BNO055 Smarthubs ASSNs Datasheet”. https://www.bosch-sensortec.com, (24.08.2017).
31. Thalmic Labs. “MYO Arm Band”. https://www.myo.com/techspecs, (24.08.2017).
32. Jazar RN. Theory of Applied Robotics. 2nd ed. London, Springer, 2010.