The public defense of Laura Gonçalves Ribeiro’s doctoral thesis was on 2 June, 2023 at Tampere University.
Title: Target Tracking Using Optical Markers for Remote Handling in ITER
Abstract:
The thesis focuses on the development of a vision system to be used in the remote handling systems of the International Thermonuclear Experimental Rector – ITER. It presents and discusses a realistic solution to estimate the pose of key operational targets, while taking into account the specific needs and restrictions of the application.
The contributions to the state of the art are in two main fronts: 1) the development of optical markers that can withstand the extreme conditions in the environment; 2) the development of a robust marker detection and identification framework that can be effectively applied to different use cases. The markers’ locations and labels are used in computing the pose.
In the first part of the work, a retro reflective marker made up ITER compliant materials, particularly, fused silica and stainless steel, is designed. A methodology is proposed to optimize the markers’ performance. Highly distinguishable markers are manufactured and tested.
In the second part, a hybrid pipeline is proposed that detects uncoded markers in low resolution images using classical methods and identifies them using a machine learning approach. It is demonstrated that the proposed methodology effectively generalizes to different marker constellations and can successfully detect both retro reflective markers and laser engravings.
Lastly, a methodology is developed to evaluate the end-to-end accuracy of the proposed solution using the feedback provided by an industrial robotic arm. Results are evaluated in a realistic test setup for two significantly different use cases.
Results show that marker based tracking is a viable solution for the problem at hand and can provide superior performance to the earlier stereo matching based approaches. The developed solutions could be applied to other use cases and applications.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 764951.