Yuri Silva
Papers
1
Total Citations
3
H-Index
1
About
Yuri Silva is a researcher focused on assistive robotics and computer vision, with a particular emphasis on indoor localization for mobility-impaired individuals. His most-cited work, "Indoor visual localization of a wheelchair using Shi-Tomasi and KLT" (2017), addresses a critical challenge in robot navigation: achieving precise positioning without expensive sensor arrays. Silva’s approach leverages a single camera combined with Shi-Tomasi feature detection and the Kanade-Lucas-Tomasi (KLT) tracker, offering a cost-effective alternative to multi-sensor fusion methods that rely on lasers, inertial units, or Wi-Fi. While his citation count (3) reflects a niche but growing interest, the work contributes to the broader goal of making autonomous wheelchairs more accessible and reliable in indoor environments. Silva’s research sits at the intersection of computer vision, human-robot interaction, and assistive technology, aiming to enhance independence for users with limited mobility. His focus on practical, low-cost solutions underscores a commitment to real-world impact, and his work serves as a stepping stone for future developments in visual SLAM and sensor-efficient navigation systems.
Research Focus
Key Achievements
Top Papers
- 1Indoor visual localization of a wheelchair using Shi-Tomasi and KLT3 citations · 2017