Lino Antoni Giefer
Papers
1
Total Citations
2
H-Index
1
About
Lino Antoni Giefer is a researcher whose work sits at the intersection of robotics, autonomous vehicles, and advanced sensor perception. His primary focus is on developing novel state estimation techniques for complex, articulated objects—a critical challenge for safe autonomous navigation. In his most cited work, "State Estimation of Articulated Vehicles Using Deformed Superellipses" (2021), Giefer introduced an innovative approach that leverages high-resolution LiDAR data to model and track the dynamic configurations of articulated vehicles, such as trucks with trailers. By representing these objects with deformed superellipses, his method enables more accurate and robust state estimation in real-world scenarios, directly addressing limitations in traditional bounding-box or point-cloud approaches. While his citation count is still building, the foundational nature of this work signals its growing relevance for researchers tackling perception in logistics, construction, and autonomous driving. Giefer’s contributions are particularly notable for bridging geometric modeling with practical sensor fusion, offering a pathway to safer, more reliable autonomous systems in environments where articulated vehicles are prevalent.
Research Focus
Key Achievements
Top Papers
- 1State Estimation of Articulated Vehicles Using Deformed Superellipses2 citations · 2021