Kevin Laubhan
Papers
2
Total Citations
10
H-Index
2
About
Kevin Laubhan's research lies at the intersection of assistive technology, computer vision, and embedded systems, with a primary focus on developing portable, low-cost navigation aids for the visually impaired. His work addresses a critical challenge: creating real-time obstacle detection systems that are both effective and practical for daily use. Laubhan's most cited paper, "Navigation assistive system for the blind using a portable depth sensor" (2015, 6 citations), pioneered the use of lightweight 3D depth sensors—typically used in robotics—for assistive devices, demonstrating their potential beyond traditional applications. He further advanced this concept with "An FPGA-based portable real-time obstacle detection and notification system" (2016, 4 citations), which tackled the engineering challenge of balancing low power consumption, portability, and cost without sacrificing performance. By leveraging FPGA technology, Laubhan showed how to process visual data efficiently in a compact form factor. Though his citation counts are modest, his contributions are notable for their practical, user-centered approach—aiming to bring high-tech solutions to millions who need them. His work represents a meaningful step toward making assistive technology more accessible and deployable in real-world environments.
Research Focus
Key Achievements
Top Papers
- 1Navigation assistive system for the blind using a portable depth sensor6 citations · 2015
- 2