Robert Lukierski
Papers
3
Total Citations
35
H-Index
3
About
Robert Lukierski is a roboticist specializing in practical, vision-based navigation for low-cost indoor robots. His research focuses on enabling small, affordable platforms—such as floor cleaners and domestic service robots—to perceive their environment with minimal hardware. Lukierski’s major contributions include developing methods for room layout estimation from rapid omnidirectional exploration (2017, 16 citations), which allows robots to globally understand room dimensions and boundaries, not just local position. He also pioneered rapid free-space mapping from a single omnidirectional camera (2015, 13 citations), integrating computer vision with SLAM for intelligent guided navigation on resource-constrained robots. Earlier, he introduced dense, auto-calibrating visual odometry from a downward-looking camera (2013, 6 citations), exploiting floor planarity for real-time, high-precision motion estimation at 30Hz using computationally efficient dense alignment. Collectively, his work demonstrates that sophisticated spatial awareness and mapping are achievable on low-cost platforms, bridging the gap between academic SLAM research and practical, deployable robotics. Lukierski’s contributions are particularly notable for their emphasis on simplicity, auto-calibration, and real-time performance, making them directly applicable to the next generation of affordable autonomous indoor robots.
Research Focus
Key Achievements
Top Papers
- 1Room layout estimation from rapid omnidirectional exploration16 citations · 2017
- 2Rapid free-space mapping from a single omnidirectional camera13 citations · 2015
- 3Dense, Auto-Calibrating Visual Odometry from a Downward-Looking Camera6 citations · 2013