Increasingly cheaper computer technology, as well as sensor and actuator systems in robotics today are paving the way for large teams of collaborating robots. The coordination of large robot teams leads to almost intractable combinatorial problems as they were never relevant in practice before. Therefore, there exists an increasing demand for time efficient approaches that are capable of solving heavy combinatorial problems as they appear in robotics and multi-agent systems today. Such problems arise, for example, in the application domains of manufacturing and intra-logistics where numerous mobile robots need to actively collaborate for managing transportation tasks. Also in search and rescue (SAR) robot coordination becomes computationally challenging with larger robot teams searching for either stationary or mobile targets, for example, when coordinating a team of unmanned aerial vehicles (UAVs) searching for lost hikers in the Alps. In this talk I will provide an overview on cognitive methods that I developed during the last years for facilitating successful collaboration in robot teams. I will provide examples from two target domains which are collaborative robots handling transportation tasks in intra-logistics, and teams of UAVs searching for survivors in Search and Rescue.
Alexander Kleiner is Universitetslektor (Assistant Professor) in the AIICS research division and leads the group on Collaborative Robotics at Linköping. He received his Ph.D. from the University of Freiburg in February 2008 and worked as an invited guest researcher at the Carnegie Mellon University, Pittsburgh, USA in 2010 and at the La Sapienza University, Rome, Italy in 2011. Since 2006, he is member of the executive committee of RoboCup (Rescue Simulation League). His research areas are autonomous robot exploration, simultaneous localization and mapping (SLAM), and mixed-initiative teams of humans and multi-robot systems. The main concern of his work is on developing reliable multi-robot/multi-agent teams coordinating and acting in real-time, and to contribute in the development of performance metrics for benchmarking their real-world applicability. He successfully participated in several international robot competitions where his teams won several times the first prize.