Roman Lavrenov
Papers
56
Total Citations
660
H-Index
14
About
Roman Lavrenov is a robotics researcher whose work spans robot simulation, autonomous navigation, and mobile robot systems — areas where he has made substantial contributions to both foundational tools and practical applications. Perhaps best known for his work on ROS/Gazebo simulation environments, Lavrenov developed automated tools for constructing realistic 3D worlds from grayscale images and sensor data, enabling faster and more cost-effective robotic algorithm development. His crawler robot modeling work, which has accumulated over 43 citations, addressed one of robotics simulation's longstanding challenges: faithfully approximating track-terrain interaction for unmanned ground vehicles. Lavrenov has also made meaningful contributions to visual SLAM, fiducial marker systems, and path planning — including Voronoi-based trajectory optimization and spline-based obstacle avoidance approaches. His 2021 survey on robotic technologies for pandemic mitigation demonstrated a broader vision for how autonomous systems can address real-world societal challenges. With a portfolio exceeding 300 cumulative citations across ten highly regarded papers, Lavrenov's research consistently bridges simulation fidelity with real-world robotic deployment, making his work particularly valuable for engineers and researchers developing and validating autonomous ground vehicle systems.
Research Focus
Key Achievements
Top Papers
- 1
- 23D modelling and simulation of a crawler robot in ROS/Gazebo43 citations · 2016
- 3Automating pandemic mitigation36 citations · 2021
- 4
- 5Comparing fiducial marker systems in the presence of occlusion30 citations · 2017
- 6Voronoi-based trajectory optimization for UGV path planning24 citations · 2017
- 7
- 8
- 9Real-Time Video Server Implementation for a Mobile Robot22 citations · 2018
- 10Modified Spline-Based Navigation: Guaranteed Safety for Obstacle Avoidance19 citations · 2017