Papers
13
Total Citations
212
H-Index
8
About
Ching-Yen Weng is a leading researcher in intelligent robotics, specializing in autonomous navigation, human-robot collaboration, and dual-arm manipulation. His work addresses critical challenges in dynamic and uncertain environments, from industrial assembly to mobile robot obstacle avoidance. Weng’s most influential paper, “Real-Time Avoidance Strategy of Dynamic Obstacles via Half Model-Free Detection and Tracking With 2D Lidar for Mobile Robots” (2020), has garnered 68 citations, showcasing its impact on safe, real-time robot navigation. He pioneered telemanipulation-based teaching methods for complex tasks like aerospace masking, enabling efficient skill transfer between humans and robots in high-mix, low-volume production. His research also includes vision-based trajectory prediction for robotic manipulation in unpredictable settings, and data-driven route generation for autonomous ships using historical AIS data. Weng has advanced dual-arm robotics through surveys and frameworks for bin packing and assembly, and introduced novel motion planning with graph Wasserstein autoencoders. His work bridges theory and practice, offering robust solutions for real-world automation.
Research Focus
Key Achievements
Top Papers
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- 3A Survey of Dual-Arm Robotic Issues on Assembly Tasks19 citations · 2018
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- 7A Framework for Robotic Bin Packing with a Dual-Arm Configuration9 citations · 2019
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