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About

Mihai Bujanca is a leading researcher in robotic perception, specializing in Simultaneous Localization and Mapping (SLAM) for dynamic environments. His work addresses a critical gap in robotics: enabling autonomous systems to operate reliably in real-world, changing scenes rather than static laboratory settings. Bujanca’s major contributions include developing robust SLAM systems that handle perturbations, with his seminal paper "Robust SLAM Systems: Are We There Yet?" (38 citations) serving as a benchmark for the field. He is a key contributor to SLAMBench 3.0 (37 citations), a standardized evaluation framework that has become essential for reproducible SLAM research. Bujanca pioneered real-time semantic 3D reconstruction of dynamic scenes with ACEFusion (9 citations), the first system to capture geometry and semantics of moving objects on robotic platforms like the Nvidia Jetson AGX Xavier. His FullFusion framework (9 citations) advanced semantic understanding of dynamic environments, while his recent NGD-SLAM (5 citations) achieves real-time dynamic SLAM without GPU dependency, democratizing access to advanced perception. Bujanca’s work consistently pushes the boundaries of what SLAM systems can achieve, making him a pivotal figure in bringing robust, real-time perception to mobile robots operating in complex, interactive environments.