Vision-Based Robotic Dance Motion Capture System

The innovative design and implementation of the human-robot collaborative dance system marks a significant breakthrough in the integration of art and technology. This system cleverly combines multi-view computer vision technology and humanoid robot control, using six high-speed cameras and an improved posture estimation algorithm to achieve high-precision human motion capture. The application of deep learning and optimization algorithms enables precise mapping of human movements onto the NAO robot. Experimental data are impressive: the average joint position error is only 14.3 mm, the action similarity score reaches 87.6%, and system latency is as low as 67 ms. These achievements not only demonstrate the enormous potential of artificial intelligence in artistic creation but also open new prospects for stage performances and human-robot interaction, heralding a promising future of technology integrated with art.