Lanke Frank Tarimo Fu
Papers
2
Total Citations
31
H-Index
2
About
Lanke Frank Tarimo Fu is a robotics researcher whose work sits at the intersection of perception, reconstruction, and autonomous navigation. His primary research areas include sensor fusion, neural radiance fields (NeRF), and robotic inspection systems. Fu’s most notable contribution is **SiLVR** (Scalable Lidar-Visual Reconstruction), a pioneering system that fuses lidar and camera data to create large-scale, geometrically accurate, and photo-realistic 3D reconstructions for robotic inspection. This work, published in 2024, has already garnered 24 citations, reflecting its immediate impact on the field. By adapting NeRF representations to handle the scale and precision demands of real-world robotics, Fu has opened new pathways for autonomous infrastructure monitoring and mapping. His more recent work, **Boxi** (2025), tackles the critical design decisions behind sensor suite configuration for robust autonomy in unstructured environments, addressing the practical engineering challenges of multimodal perception. Fu’s research is characterized by a rare ability to bridge cutting-edge computer vision techniques with tangible robotic applications, making his contributions equally valuable to theorists and practitioners. His work on SiLVR, in particular, stands as a benchmark for scalable, high-fidelity reconstruction in robotics.
Research Focus
Key Achievements
Top Papers
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- 2