Ming-Chang Chen
Papers
6
Total Citations
51
H-Index
4
About
Ming-Chang Chen is a robotics researcher whose work focuses on autonomous mobile robot navigation, particularly in challenging indoor environments. His primary contributions lie in developing practical, vision-based systems for robot self-localization, obstacle avoidance, and autonomous stair climbing. Chen’s most cited work, a 2014 paper on mobile robot self-localization using a single webcam (21 citations), introduced a cost-effective distance measurement technique that leverages existing surveillance infrastructure. He has also made notable advances in tracked robot mobility, with papers on autonomous stair detection and climbing (13 citations) and wall-following systems (6 citations), enabling robots to traverse stairs, slopes, and uneven terrain. His research extends to intelligent control, including adaptive PD fuzzy control for balancing robotic arms and fuzzy measure-based controllers for movement. While his citation counts are modest, Chen’s work is characterized by its emphasis on practical, implementable solutions—using readily available sensors like webcams and Kinect—to solve real-world robotic mobility challenges. His contributions are particularly relevant for researchers working on low-cost, autonomous navigation systems for service and inspection robots.
Research Focus
Key Achievements
Top Papers
- 1
- 2Autonomous stair detection and climbing systems for a tracked robot13 citations · 2013
- 3
- 4Image-based obstacle avoidance and path-planning system5 citations · 2013
- 5
- 6