Zhuotao Feng
Papers
1
Total Citations
1
H-Index
1
About
Zhuotao Feng is a researcher focused on advancing robotic perception and precision control in construction automation. His key contributions lie in developing robust visual algorithms for real-world construction environments, particularly for laser-based positioning systems. In his most cited work, "Positioning Laser Line Detection Algorithm of Construction Robot Based on LSD and Improved Least Squares Method" (2023), Feng addresses critical challenges in construction robotics by proposing a novel algorithm that combines Line Segment Detector (LSD) with an enhanced least squares method. This approach significantly improves the accuracy and reliability of laser line detection during actual construction operations, enabling robots to perform precise localization tasks. The algorithm effectively handles noise and edge detection issues common in unstructured construction sites. While his work is still gaining recognition, with 1 citation to date, Feng's research demonstrates the potential for computer vision techniques to bridge the gap between laboratory robotics and practical construction applications. His contributions are particularly valuable for the growing field of automated construction, where robust perception systems are essential for tasks like material handling, surface inspection, and autonomous navigation in complex building environments.
Research Focus
Key Achievements
Top Papers
- 1