Yoseph Yang
Papers
6
Total Citations
31
H-Index
3
About
Yoseph Yang is a robotics researcher whose work spans vision-based perception, mobile manipulation, and autonomous navigation. His most impactful contribution is a novel ball tracking and trajectory prediction system for tennis-playing robots (16 citations), which addresses the challenge of enabling robots to interact dynamically with fast-moving objects in sports environments. Yang also developed a visual odometry algorithm that uses template matching to estimate a robot’s absolute position in known environments, enhancing localization accuracy without relying on GPS. His practical innovations include designing and 3D printing a low-cost mecanum mobile manipulator, making collaborative robotics more accessible for university research and education. Additionally, he has applied Model Predictive Control to autonomous delivery robots, improving their high-speed mobility by managing inertial and centrifugal forces. Yang’s work on wheel-visual-inertial odometry further tackles indoor localization in environments with limited features. With a focus on cost-effective, real-world robotic systems, his research demonstrates how vision, control, and mechanical design can be integrated to create robots that perceive, move, and interact more intelligently.
Research Focus
Key Achievements
Top Papers
- 1Ball tracking and trajectory prediction system for tennis robots16 citations · 2023
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