Min-Long Tsai
Papers
1
Total Citations
2
H-Index
1
About
Min-Long Tsai’s research bridges robotics, computer vision, and automation, with a focus on enabling machines to perceive and manipulate challenging objects. His most-cited work, “Robotic Arm Combined with the Visual Images in a Transparent Object Recognition” (2020), tackles a notoriously difficult problem in industrial robotics: recognizing and grasping transparent objects. By integrating a robot-mounted camera with LabView-based coordinate transformation, Tsai developed a system that allows robotic arms to identify and pick transparent bottles—a task that often confounds conventional vision systems due to reflections and lack of texture. This contribution, demonstrated with four distinct bottle types, has practical implications for manufacturing, logistics, and recycling automation. While his citation count is modest, the work addresses a critical gap in perception-driven robotics, laying groundwork for more robust object recognition in cluttered or visually ambiguous environments. Tsai’s research exemplifies how targeted, application-oriented engineering can solve real-world industrial challenges, and his findings offer a foundation for future advances in transparent object manipulation and human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1