PhD Thesis “3D Inspection and Measurement by Path Planning and Robotic-Assisted Vision”

Updated: about 17 hours ago

As

Austria's largest research and technology organisation for applied research

, we are dedicated to making substantial contributions to solving the major challenges of our time, climate change and digitization. To achieve our goals, we rely on our specific research, development, and technology competencies, which are the basis of our commitment to excellence in all areas. With our open culture of innovation and our motivated, international teams, we are working to position AIT as Austria's leading research institution at the highest international level and to make a positive contribution to the economy and society.

Our

Center for Vision, Automation & Control

 located in Vienna invites applications a PhD Thesis. The Center exploits the opportunities provided by

automation and digitization

to initiate and advance innovation for industry, primarily in Austria and Europe. Our main goal is to take away the monotonous, heavy, difficult, and dangerous aspects of people’s work through innovation. We help our partners by making technical systems more robust, reliable, flexible, and easy to use. At the same time, we increase the resource efficiency of industrial processes by reducing waste, product failures and emissions.

For this PhD project, you will become a team member of both the Competence Units

High-Performance Vision Systems (HVS) and Complex Dynamical Systems (CDS)

. In HVS, we

develop 2D & 3D vision systems that go beyond the state of the ar

t, by

developing advanced vision sensor concepts

, designing

scalable embedded vision systems

, and

applying machine learning methods to conduct high-performance visual quality inspections of products in manufacturing plants and production processes

. At present, we are transferring our machine vision knowledge to the

domain of robotic-assisted inspection

by

creating novel sensor solutions

. In CDS, we are focusing on the development and deployment of algorithms to control various types of systems, starting from low-energy applications such as electronics and drive systems, via

robotics to heavy industrial applications

.

The objective of this PhD project is to develop and validate design concepts for robotic-assisted, automated vision-based inspection and measurement for complex 3D shapes. The automation of quality inspection in manufacturing is critical for directly assessing product quality features, such as dimensional accuracy (geometry) and surface defects, which are traditionally gauged through costly and time-consuming methods like tactile 3D systems or computed tomography, or subjective manual inspection by trained workers. At the AIT's Center for Vision, Automation & Control, we have long-standing experience in lab prototype development of vision-based inspection systems for products of the manufacturing industry, with a recent shift towards more complex use cases such as die-casted and injection-moulded parts. To this end, we have developed algorithms for viewpoint planning and 3D reconstruction of optical sensor data and built a vision-based multi-axis laboratory prototype to deploy and test those algorithms for the inspection of complex 3D parts. As part of a bigger team in our Competence Units, you will further improve the handshake between robotics & vision and embrace continuous path planning and accuracy & precision metrics for inspection of complex 3D shapes, which orchestrates the movement of a robot or sensor along a seamless path for continuous inspection to speed up inspection processes and includes the development of vision-based metrology approaches & measurement tools for quality control, respectively.
Join our AIT PhD programme with around 150 international students, carried out in cooperation with renowned universities, including namely the TU Wien. This PhD project is part of the Lighthouse Project Sustainable Manufacturing of High-Quality Products, where we develop new methods and technologies to enable zero-defect manufacturing. You will thus have the unique opportunity to work on relevant real-world problems that arise in ongoing cooperation with national and international research organizations and companies that are leading their market sectors.



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