Boill Chun
Papers
1
Total Citations
10
H-Index
1
About
Boill Chun is a researcher whose work sits at the intersection of robotics, automation, and building maintenance systems. Their key research areas include robotic perception, contamination detection, and the development of intelligent maintenance solutions for built environments. Chun’s most notable contribution is the development of a novel window contamination detection method for robotic building maintenance systems, a foundational piece of work that has garnered 10 citations since its publication in 2011. This research, presented at the 28th International Symposium on Automation and Robotics in Construction (ISARC), addresses a critical challenge in automating building facade cleaning—enabling robots to accurately identify and respond to surface contamination. By integrating sensor-based detection with robotic control systems, Chun’s work has helped advance the practical deployment of autonomous maintenance robots, reducing the need for human intervention in hazardous or high-rise environments. While their published output is focused, the impact of this single, well-cited paper demonstrates Chun’s ability to solve a specific, real-world problem with clear engineering and commercial relevance. For students and researchers in construction robotics and building automation, Chun’s work offers a valuable case study in bridging perception and action for practical robotic systems.
Research Focus
Key Achievements
Top Papers
- 1