My general research interest is in developing reliable solutions for navigation and coordination problems of large robot teams operating in real-world environments. I see myself in between a theory and a systems person, and have a track record of developing new conceptual approaches for autonomous systems that were deployed in real environments. For example, I developed together with my students several multi-agent and multi-robot systems that successfully competed during international competitions in robotics, a mapping system for the commercial bomb disposal robot Telemax, and a fully autonomous navigation and coordination system for robot teams solving intra-logistics tasks that is currently on the way of being transferred to industry.
Besides my claim to develop methods for systems that persist in real environments, my goal is to contribute to the development of the theoretical foundations of methods for team collaboration in multi-agent systems and robotics. Multi-robot setups are becoming increasingly interesting also from a theoretical perspective. Due to the advent of more and more sophisticated sensors and actuators in robotics, the deployment of significantly larger robot teams comes into reach leading to almost intractable combinatorial problems as they were not relevant before. Particularly in manufacturing and intra-logistics, methods for task assignment and task sequencing are needed that work both close-to-optimal and in real-time. In the Search And Rescue (SAR) domain algorithms for computing efficiently close-to-optimal assignments of heterogenous teams to tasks are more and more demanding.
My overall research plan is to develop the theoretical foundations for unifying existing, loosely coupled approaches in task allocation and team formation into a single solution concept. Consequently, to improve the existing formalisms for team collaboration towards applicability in settings as they are found in the real-world.