Dmitry Zhukov

Samsung (Russia), Samsung (United States)

Papers

Total Citations

H-Index

About

Dmitry Zhukov is a robotics and computer vision researcher whose work centers on simultaneous localization and mapping (SLAM), indoor navigation, and the development of benchmarking resources for autonomous systems. His research addresses some of the most practical challenges facing mobile robotics today — namely, how reliably visual SLAM systems perform in real-world indoor environments. His most cited contribution, "Measuring Robustness of Visual SLAM" (2019, 58 citations), offers a rigorous feasibility study of RGB-D SLAM applied to indoor robot navigation, critically evaluating state-of-the-art methods such as ORB-SLAM2 and shedding light on their limitations under realistic conditions. This work has become a valuable reference for researchers seeking honest benchmarks of visual odometry systems. Complementing this, Zhukov co-created DISCOMAN — a richly detailed dataset of 200 indoor sequences, each containing thousands of frames generated from realistic home layouts — designed specifically to advance training and evaluation of semantic SLAM methods. Together, these contributions reflect a consistent commitment to grounding autonomous navigation research in rigorous, reproducible evaluation. His work is particularly valuable for graduate students and practitioners building robustly deployable robotic systems.