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 digitalisation. 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(VAC) is looking for new Ingenious Partner for our location in Vienna. The Center for Vision, Automation & Control exploits the opportunities provided by automation and digitalisation 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.

The automation of work machines, such as cranes and forklift trucks, is a strategic research goal at VAC. In the future, these machines will take over repetitive and dangerous tasks. The aim is twofold: firstly, to relieve the burden on employees and enhance their role, as they will be responsible for planning and monitoring in the future, and secondly, to counteract the shortage of skilled workers. To enable automation, many complex issues need to be investigated, ranging from environment recognition and interpretation to machine control and human-machine interaction. For validation and testing purposes, the AIT has set up its own open-air test site for autonomous machines in Seibersdorf.

• This thesis addresses the challenge of kinematic state estimation in large-scale manipulators that suffer from elastic deformation. Due to high loads and lightweight construction, these systems experience systematic errors in gripper pose estimation when relying solely on joint encoders for forward kinematics.
• By integrating exteroceptive sensors like LiDAR with proprioceptive joint measurements, correct these errors.
• You will investigate, integrate and benchmark multiple state algorithms fusing LiDAR and odometry measurements.

• Under the guidance of our team, you will evaluate the practical feasibility on a real-world forestry crane in AITs Large-scale Robotics Lab.
• You will broaden your knowledge and skills in the field of state estimation, ROS integration, and perception & decision-making.
• You will train in scientific work and can discuss your experiences with scientific interdisciplinary experts from the field of AI & robotics.
• You may publish your results at a conference or in a journal.