Yu-Cheng Wang
Papers
1
Total Citations
4
H-Index
1
About
Yu-Cheng Wang is a robotics researcher whose work focuses on low-cost, practical localization and sensing solutions for mobile robots, particularly those equipped with omnidirectional Mecanum wheels. His most cited paper, "Global Localization Using Dead-Reckoning and Kinect Sensors for Robots with Omnidirectional Mecanum Wheels" (2014, 4 citations), introduces a novel method that fuses dead-reckoning data with Kinect sensor measurements using a least-squares approach and an extended Kalman filter (EKF). This technique enables accurate global pose estimation for an anthropomorphous dual-arm mobile robot (ADAMR) in indoor environments, addressing a key challenge in affordable robotics. By leveraging off-the-shelf sensors, Wang’s work demonstrates how to achieve reliable localization without expensive equipment, making advanced robotic capabilities more accessible. His contributions are particularly valuable for researchers and students interested in sensor fusion, mobile robot navigation, and cost-effective automation, offering a practical framework that balances precision and affordability in real-world applications.
Research Focus
Key Achievements
Top Papers
- 1