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JOIN OUR LIVE EVENT
When: Wednesday, 20.11.2024 | 12 pm (CET)
Topic: Explore PhD & Career Options @ AIT - From Students to Researchers & Innovators! 
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As Austria's largest research and technology organisation for applied research, we are dedicated to make substantial contributions to solving the major challenges of our time, climate change and digitisation. 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 for a master’s thesis. The Center for Vision, Automation & Control exploits the opportunities provided by automation and digitisation 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.
 
Our Competence Unit Complex Dynamical Systems focuses on the development and deployment of algorithms to control various types of systems. Starting from low energy applications like electronics and drive systems, via (large-scale) robotics to heavy industrial applications. We are working in projects in cooperation with national and international research organisations and companies leading their market sector.

• Forestry cranes are heavy vehicles used for complex manipulation tasks in cluttered forest environments, such as lifting logs from the ground onto a timber trailer. In general, a forestry crane exhibits a complex system dynamic. Furthermore, the unpredictable and rough forest terrain yields an additional challenge for automation.
• The objective of master thesis is to apply a deep dynamic motion primitive (deep-DMP) approach to a forestry crane for the online motion planning in manipulation scenarios.
• First, a literature review of the developments in forestry automation and in the field of dynamic motion primitives will be conducted. The scientific and technological challenges will be explored as well as the opportunities for research and applications.
• The second step is to study the kinematics and dynamics of the considered forestry crane. Additionally, a physics-based simulation environment will be used (Algoryx and/or Mujoco).

• In the main step, the encoded motion data is built using dynamic motion primitives. A Machine-Learning approach is trained that takes into account both the encoding motion data and the image data to adapt learned skills to different situations.
• You will broaden your knowledge and skills in the field of motion planning, machine learning, computer vision, and automation & control theory.
• You will train in scientific work and have the opportunity to discuss your experiences with scientific interdisciplinary experts from the field of automation & control, machine learning.
• You may publish your results at a conference or in a journal.