The project of "Human-Robot Dance" targets intuitive, no-code robotic arm control, enabling artists to co-create using body language. Two main workflows were developed: Teach (Offline), where a dancer＇s movements are captured, processed, translated, and then reproduced by the arm; and Mirror (Online), where real-time pose perception and data translation allow the arm to synchronously mimic the dancer for improvisational co-dance.

The “Human-Robot Co-Dance＇” project lie in: empowering artists with code-free, intuitive robot choreography tools. Through real-time motion capture and Inverse Kinematics, coupled with node translation via machine learning, it achieves human-robot synchronous mirroring and a deeply coupled interaction. Ultimately, through co-creation and co-choreography, it explores the ＇pseudo-life＇ characteristics of robots, pioneering a new direction for techno-art creation through co-dance.

This project＇s technologies including intuitive robot teaching, real-time motion capture, and AI-driven motion translation offer vast potential. In Human-Robot Collaboration, they address skill gaps in smart manufacturing and construction, enabling flexible, safe co-working and fostering digital craftsmanship. In Techno Art, these tools empower artists with direct, intuitive expression, creating novel interactive experiences and allowing exploration of Human-Robot Co-Creation.