Li-Chia Yeh

About

Li-Chia Yeh is a researcher at the forefront of intelligent robotics and automation, with a particular focus on integrating deep learning and optimization to enhance robotic manipulation. His work addresses a critical bottleneck in robotics: the time-consuming and labor-intensive process of collecting real-world training data. In his most-cited study, "Developing an automatic gripping learning system for a robotic arm by integrating a convolutional neural network and optimization algorithms" (2025, 5 citations), Yeh pioneered a method that uses optimization algorithms to automatically detect optimal gripping positions in a simulated environment. This approach generates high-quality training data without the need for physical trials, dramatically reducing the difficulty and time required for real-world data collection. By designing a system that learns to grip objects through simulation-driven data, Yeh has made a significant contribution to making robotic learning more efficient and scalable. His work holds promise for advancing autonomous manufacturing, logistics, and service robotics, and marks him as an emerging innovator in the field of intelligent robotic systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Developing an automatic gripping learning system for a robotic arm by integrating a convolutional neural network and optimization algorithms

   5 citations · 2025

Key Collaborators

Contact & Links