Master Thesis - Imitation Learning for Industrial Robotics

the opportunity to work in a dynamic and collaborative environment, where you can test and validate new technologies, methods, and solutions in close collaboration with our internal and external stakeholders. To learn more about the Smart Factory, visit [Link](https://www.scania.com/group/en/home/innovation/research/smart-labs.html). **Assignment** The objective is to investigate how different training and data-collection factors influence the performance, robustness, and generalisation of imitation-learned robot policies across relevant industrial use cases. Using the existing robotic test setup, the students will select one or more relevant robot tasks and conduct structured experiments. The work may include: - Collecting and preparing demonstration data. - Investigating the required amount and variation of demonstrations. - Evaluating policy performance on different physical setups and environmental conditions. - Documenting the results and developing recommendations for future applications. **Background and Time Plan** Experience with Python, ROS, robot programming, CAD modelling, computer vision, or machine-learning frameworks, is beneficial but not necessarily required. - Students in Robotics or Engineering, who bring some background in AI training. - Computer Science students who are eager to build physical prototypes. **Number of students** **:** 1-2 **Start date** **:** January 2027 (20 weeks) **Location** **:** Södertälje, Sweden (at least 60% on-site) Requisition ID: 33505 Number of Openings: 2.0 Part-time / Full-time: Full-time Permanent / Temporary: Temporary Country / Region: SE Location(s): Södertälje, SE, 151 38 Required Travel: 0% Workplace: On-site [Apply now »](https://jobs.scania.com/talentcommunity/apply/1443169133/?locale=en_US)