# Robotics and Semantic Systems (RSS), Lund University > Robotics and Semantic Systems (RSS) is a research division at the Department of Computer Science, Faculty of Engineering (LTH), Lund University, Sweden. It works on robotics, artificial intelligence and natural language processing: robot learning and foundation models, human-robot interaction, perception, multimodal AI and privacy, medical, construction and humanoid robotics. The division also runs RobotLab LTH and teaches AI, machine learning and robotics courses. ## About the division RSS has 11 faculty members and 11 doctoral students (25 current members in total). Research is organised in 7 research themes, each led by a faculty member, and carried out in externally funded projects with industrial and academic partners such as ELLIIT, WASP, Vinnova, the Swedish Research Council and the Knut and Alice Wallenberg Foundation. Experimental work takes place in RobotLab LTH, a shared lab with dual-arm and single-arm manipulators, mobile platforms, autonomous model cars and sensing rigs. - Postal address: Robotics and Semantic Systems, Department of Computer Science, Lund University, Box 118, SE-221 00 Lund, Sweden - Visiting address: Klas Anshelms väg 10/Ole Römers väg 3, SE-223 63 Lund, Sweden - Email: expedition@cs.lth.se - [Contact and about page](https://pages.git.cs.lth.se/rss/website/about/) ## Research themes - [Foundation Models and Visuomotor Policies](https://pages.git.cs.lth.se/rss/website/research-themes/foundationmodels/): Connecting foundation models and learned robot skills with explicit world models and explainable task control. Led by Volker Krueger. - [Human-Robot Interaction & Collaborative Robotics](https://pages.git.cs.lth.se/rss/website/research-themes/hri-collaborative-robotics/): Mixed-initiative interaction, situation awareness in shared autonomy, knowledge representation for intuitive instruction of robots, and physical human-robot interaction. Led by Elin A. Topp. - [Perception & Autonomous Systems](https://pages.git.cs.lth.se/rss/website/research-themes/perception-autonomous-systems/): Learning semantic representations from visual experiences to enable more robust perception and intelligent action execution in autonomous systems. Led by Eren Aksoy. - [Multimodal AI and Privacy](https://pages.git.cs.lth.se/rss/website/research-themes/language-tech-privacy/): Parsing, language models and language as a robot interface, and what happens to text when personal data must be removed from it. Led by Xuan-Son (Sonny) Vu. - [AI and Robotics in Medicine](https://pages.git.cs.lth.se/rss/website/research-themes/ai-robotics-in-medicine/): Computer vision and autonomous robots in clinical settings, from surgical instrument tracking to robotized instrument handovers. Led by Maj Stenmark. - [Construction Robotics](https://pages.git.cs.lth.se/rss/website/research-themes/construction-robotics/): Mobile robots that measure, set out and report back from the building site. Led by Mathias Haage. - [Humanoid Robots](https://pages.git.cs.lth.se/rss/website/research-themes/humanoids/): Bringing humanoid robots into the real world, enabling them to react and adapt to dynamic environments. Led by Davide Tateo. ## Current projects - [Advanced Physical AI Technology with Humanoid Robots for Manufacturing, Healthcare, and Lab Automation](https://pages.git.cs.lth.se/rss/website/projects/humanoid-physical-ai-infrastructure/): PI Davide Tateo; funded by LTH; 2027–2029. - [A Robust and Reliable Vision-Language-Action Interface](https://pages.git.cs.lth.se/rss/website/projects/vla-interface/): PI Per-Erik Forssén (Linköping University), Volker Krueger; funded by ELLIIT; 2026–2030. - [Safe Reinforcement Learning of Humanoid Locomanipulation Policies](https://pages.git.cs.lth.se/rss/website/projects/tateo-crafoord/): PI Davide Tateo; funded by Crafoord Foundation; 2026–2027. - [MSynth: Scalable Synthetic Data Generation for Multimodal AI](https://pages.git.cs.lth.se/rss/website/projects/msynth/): PI Xuan-Son (Sonny) Vu; funded by Knut and Alice Wallenberg Foundation; 2026–2028. - [MOUSE: Multimodal Multitask Learning for Reliable Robot Situational Awareness in Adverse Environmental Conditions](https://pages.git.cs.lth.se/rss/website/projects/mouse/): PI Eren Aksoy; funded by ELLIIT; 2026–2030. - [An Agentic Approach to Mixed Initiative Multi-Robot Interaction for Public Safety Applications](https://pages.git.cs.lth.se/rss/website/projects/mixed-initiative-multi-robot-public-safety/): PI Elin A. Topp; funded by ELLIIT; 2026–2030. - [Mormor Karl är 27 år: automatisk pseudonymisering av forskningsdata](https://pages.git.cs.lth.se/rss/website/projects/mormor-karl/): PI Xuan-Son (Sonny) Vu; funded by Swedish Research Council; 2025–2029. - [Efficient Transfer Learning for Robot Skills](https://pages.git.cs.lth.se/rss/website/projects/efficient-transfer-learning/): PI Volker Krueger, Maj Stenmark; funded by Vinnova, through the NextG2Com competence centre; 2025–2030. - [Bi-manual Robot Learning](https://pages.git.cs.lth.se/rss/website/projects/bi-manual-robot-learning/): PI Maj Stenmark, Volker Krueger; funded by Wallenberg Autonomous Systems Program (WASP); 2024–2029. - [CAISA: Collaborative AI Surgical Assistant](https://pages.git.cs.lth.se/rss/website/projects/caisa/): PI Maj Stenmark; funded by Vinnova; 2024–2027. - [Get a Grip: Accurate Robot–Human Handovers](https://pages.git.cs.lth.se/rss/website/projects/get-a-grip/): PI Elin A. Topp, Maj Stenmark; funded by Wallenberg AI, Autonomous Systems and Software Program (WASP); 2024–2029. - [NextG2Com: Next Generation Communication and Computational Infrastructures and Applications](https://pages.git.cs.lth.se/rss/website/projects/nextg2com/): PI Volker Krueger, Maj Stenmark; funded by Vinnova; 2024–2028. ## Teaching and theses - [Courses](https://pages.git.cs.lth.se/rss/website/education/courses/): Courses taught by the division at LTH, including Artificial Intelligence, Applied Machine Learning, Intelligent Autonomous Systems and Language Technology. - [Available master thesis projects](https://pages.git.cs.lth.se/rss/website/education/available-master-thesis/): Open thesis proposals, often with an industrial partner. - [Finished master theses](https://pages.git.cs.lth.se/rss/website/education/finished-master-thesis/): Completed theses supervised in the division, from LUP Student Papers. ## Key pages - [Home](https://pages.git.cs.lth.se/rss/website/): Front page with highlights and recent news. - [Research](https://pages.git.cs.lth.se/rss/website/research/): Overview of all research themes and their members. - [RobotLab](https://pages.git.cs.lth.seresearch/robotlab/): The division's robotics laboratory and its equipment. - [Projects](https://pages.git.cs.lth.seprojects/): Current and past research projects. - [People](https://pages.git.cs.lth.sepeople/): Faculty, research engineers and doctoral students, with research themes and contact details. - [Publications](https://pages.git.cs.lth.se/rss/website/publications/): Selected recent publications. - [Demos and videos](https://pages.git.cs.lth.sevideos/): Robot demonstrations from RobotLab LTH. - [News](https://pages.git.cs.lth.se/rss/website/news/): Announcements, new projects, defences and new staff. ## Recent news - [New project: MOUSE, multimodal perception for robots in adverse conditions](https://pages.git.cs.lth.se/rss/website/news/2026/06/01/mouse-project-starts/): 2026-06-01. - [Simon Kristoffersson Lind defends thesis on uncertainty estimation for robotic vision](https://pages.git.cs.lth.se/rss/website/news/2026/01/15/uncertainty-estimation-thesis-and-gpify/): 2026-01-15. - [Welcome Stefan](https://pages.git.cs.lth.se/rss/website/news/2023/05/08/welcome-stefan/): 2023-05-08. - [Welcome Ayesha](https://pages.git.cs.lth.se/rss/website/news/2022/05/10/welcome-ayesha/): 2022-05-10. - [svt.se: Robothunden Buster hjälper till på bygge](https://pages.git.cs.lth.se/rss/website/news/2022/01/03/svt-robothunden-buster/): 2022-01-03. ## Optional - [Lund University Research Portal](https://portal.research.lu.se/en/organisations/robotics-and-semantic-systems/): Authoritative list of the division's publications, projects and staff profiles. - [LUP Student Papers](https://lup.lub.lu.se/student-papers/search/organization/V1000170): Master's theses from the Faculty of Engineering. - [RobotLab LTH website](https://www.robotics.lth.se): The lab's own website. - [YouTube channel](https://www.youtube.com/@roboticsLTH): Robot demonstration videos. - [News feed](https://pages.git.cs.lth.sefeed.xml/): Atom feed of news posts.