Papers
2
Total Citations
15
H-Index
2
About
Yilong Yang is a pioneering researcher at the intersection of robotics, intelligent textiles, and human-machine interaction. His work focuses on two transformative areas: generative AI for robotic motion learning and self-powered wearable sensing systems. In robotic calligraphy, Yang introduced a groundbreaking GAN-based motion learning framework that enables robots to synthesize complex, artistic brushstrokes—moving beyond simple character writing to capture the fluidity and expressiveness of human calligraphy (10 citations). This work bridges creative AI with precision robotics, opening new avenues for artistic automation. Simultaneously, Yang developed a wearable self-powered intelligent textile (WSIT) that integrates triboelectric nanogenerators (TENGs) with optical–electrical dual-mode sensing (5 citations). This innovation allows for real-time pressure distribution detection and remote control without external power sources, with applications spanning intelligent robotics, augmented reality, and smart homes. By merging energy harvesting with multimodal sensing, Yang’s contributions advance both autonomous systems and wearable technology, demonstrating how AI-driven motion learning and self-powered textiles can reshape interactive robotics and human-centered devices.
Research Focus
Key Achievements
Top Papers
- 1
- 2