The Rudiger Dillmann Lab

Dillmann Lab develops robotics and autonomous systems for difficult real-world tasks, especially in walking robots, mobile exploration, manipulation, and human-robot collaboration. The group works on robots that can operate in complex and changing environments, from industrial workspaces to disaster-response and planetary-exploration scenarios. A major theme is robust autonomy: the lab studies how robots can plan paths in 3D, explore unknown spaces, estimate what areas can be covered, react safely to unexpected failures, and choose informative next actions when time and data are limited. Another strong line of work focuses on perception and learning, including few-shot recognition of tools, vision-based 3D reconstruction, active learning for robot missions, trash segmentation, and data-driven adaptation of walking behavior. The lab also addresses planning and decision-making for assembly, disassembly, and cooperation with humans, where flexibility and safety matter as much as efficiency. Students can expect hands-on work with real robots, simulations, computer vision, machine learning, motion planning, and field experiments. The research is practical and system-oriented, with an emphasis on making robots more capable, adaptable, and useful in the real world.