Papers
1
Total Citations
20
H-Index
1
About
Ivan Leplumey is a computer vision researcher whose work focuses on autonomous robot navigation, particularly in indoor environments. His key research areas include monocular vision-based landmark detection, robot localization, and real-time environmental perception. Leplumey’s most cited work, "Simple monocular door detection and tracking" (2013, 20 citations), addresses a fundamental challenge in indoor robotics: enabling a robot to navigate corridors without relying on pre-existing maps or prior knowledge of the environment. By developing a method to detect and track doors as reliable landmarks using only a single camera, he contributed a practical, low-cost solution for autonomous navigation in structured indoor spaces. This approach is especially valuable for service robots and assistive technologies operating in hospitals, offices, or homes. While his citation count reflects a focused, early-stage contribution, the work’s emphasis on simplicity and real-time performance has made it a useful reference for researchers exploring minimal-sensor navigation. Leplumey’s research underscores the importance of robust landmark extraction in monocular vision, a critical step toward fully autonomous indoor robots.
Research Focus
Key Achievements
Top Papers
- 1Simple monocular door detection and tracking20 citations · 2013