Mikhail Sizintsev

SRI International, Vision International University

Papers

Total Citations

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About

Mikhail Sizintsev is a robotics researcher specializing in autonomous navigation for visually-degraded environments—settings where traditional cameras fail, such as smoke-filled disaster zones or dark infrastructure tunnels. His work centers on multi-sensor fusion, semantic SLAM, and ranging-aided navigation, addressing critical challenges in GPS-denied conditions. In his most-cited paper (2019, 10 citations), Sizintsev demonstrated how low-cost sensor fusion enables accurate motion estimation for ground robots during infrastructure inspection and indoor rescue missions. He advanced this with SIGNAV (2022, 7 citations), a semantically-informed SLAM system that maintains performance in visually-degraded environments by understanding perceived scenes—a key limitation of current vision-based systems. His 2022 work on UWB ranging (4 citations) further innovated by enabling navigation using ranging nodes at unknown locations, removing the need for pre-surveyed infrastructure. These contributions directly impact real-world deployment of autonomous robots in time-pressed, hazardous scenarios. Sizintsev’s research bridges the gap between theoretical SLAM and practical field robotics, making him a notable figure in resilient navigation for first responders and industrial automation.