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About

Miroslav Kulich is a prominent robotics researcher whose work spans autonomous mobile robotics, environmental mapping, multi-robot systems, and robotics education. Based at the Czech Technical University in Prague, his contributions have shaped how robots perceive, navigate, and collaboratively explore unknown environments. Kulich's early work on robust data fusion with occupancy grids (74 citations) addressed the critical challenge of building accurate environmental models from multiple sensor inputs — a foundational problem in autonomous navigation. His bearing-only navigation system (72 citations) demonstrated that reliable monocular robot navigation could be achieved with elegant simplicity, requiring no sensor calibration and minimal computational overhead. A significant thread of Kulich's research focuses on multi-robot exploration, where his investigations into goal assignment strategies, frontier-based exploration benchmarking, and distance utility functions (collectively accumulating over 190 citations) have meaningfully advanced how robot teams efficiently map unknown spaces. His spatiotemporal search approach further extended these ideas to tracking non-stationary objects. Beyond core robotics, Kulich has made notable contributions to robotics education through SyRoTek (72 citations), an innovative remote-access e-learning platform enabling students worldwide to experiment with real mobile robots. His association with the European Robotics Symposium 2008 (295 citations) underscores his standing within the broader European robotics community, making him a significant figure in both research and educational advancement in the field.