Development of a Framework for an Automated Mechanical Testing Automatic specimen tray detection and handling procedure using a robotic manipulator. D. S. Nunes (a), A. G. Andrade-Campos (b) , and M. R. Oliveira (c) (a), (b), and (c) - Dept. of Mechanical Engineering; University of Aveiro. (a), (b), and (c) - Aveiro, Portugal. (a) – diegonunes@ua.pt, (b) – gilac@ua.pt, and (c) – mriem@ua.pt Abstract — Nowadays, predict or characterize material's behaviour are arduous tasks which involve performing repetitive tests in material testing. When executed manually, they result in inaccurate data, due to the repeatability of the process. However, these handling specimen tasks could be performed automatically using traditional robotic manipulators, and creating systems based on automatic mechanical testing [1, 2]. Consequently, the precision of the testing results can increase, as well as the automatism of the processes and the test's throughput. Some commercial products are already available on the market, but these options are offered as entire closed-source solutions (hardware and software) and cannot adapt themselves to existing equipment or retrofitted systems. In this work, it is created a communication infrastructure between the equipment to be included in the automatic system designed [3]. The whole process is managing the interface communication between devices and, consequently, composing the automatic material testing routine. This requires implementing several changes in the testing machine selected aiming to increase its degree of automation and, consequently, allow further integration in the fully automatic testing procedure. Additionally, a visual perception system is created using a specimen tray randomly positioned on a workspace, which includes a camera and robotic manipulator that is automatically operating the traditional specimen handling of testing (picking task). Here, a visual board reference (ChArUco board contained in the specimen tray) is detected by a machine vision procedure and the final picking coordinates of each specimen within the tray is obtained, in the manipulator’s coordinate system format (through the relation of multiple geometric transformations). The calibration methods are accomplished using ROS framework and the final system achieved operates in automatic mode, handling specimens from the tray prototype (designed for this work) to a fixed position previously taught to the manipulator, which represents the exact feeding position on machine tests [4]. In the end, the results obtained allow the validation of the procedure created and its potential to be included in fully automated material testing systems to be designed in the future. Keywords — Specimen handling; Automation; Material Testing; Robotic Manipulator; Tray Detection; Machine Vision; ChArUco board.
ACKNOWLEDGEMENTS
This work is supported by the projects: UID/EMS/00481/2019-FCT - FCT - Fundação para a Ciência e a Tecnologia; and CENTRO-01-0145-FEDER022083 - Centro Portugal Regional Operational Program (Centro2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund. TOPIC 1) Sustainable Manufacturing Solutions a. Manufacturing Processes & Simulation REFERENCES [1] A. Sadiki, T. Ortelt, C. Pleul, C. Becker, S. Chatti, and A. E. Tekkaya, “The challenge of specimen handling in remote laboratories for engineering education,” 12th Internation Conference on Remote Engineering and Virtual Instrumentation, February 2015. [2] T. Ortelt, A. Sadiki, C. Pleul, C. Becker, S. Chatti, and A. E. Tekkaya, “Development of a tele-operative testing cell as a remote lab for material characterization,” In: Proceedings of 2014 in International Conference on Interactive Collaborative Learning (ICL). Reprint by Springer International Publishing AG. 2016, in press. [3] D. S. Nunes, “Development of a framework for an automated mechanical testing,” M.S. thesis, University of Aveiro, Dec. 2020. [4] D. S. Nunes, “Automated Testing System - Tray Tracking & Specimen handling (3/3),” YouTube, 11-Nov-2020. [Online]. Available: https://www.youtube.com/watch?v=qlHQGAHaHng. [Accessed: 17-Dec-2020].
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