Liqian Lai

Papers

Total Citations

H-Index

About

Liqian Lai’s research lies at the intersection of robotics, artificial intelligence, and performing arts, with a focus on enabling robots to autonomously generate expressive, music-driven choreography. In their most-cited work, “Plan2Dance: Planning Based Choreographing from Music” (2020, 3 citations), Lai addresses a critical gap in dancing robot systems: the ability to plan and sequence movements beyond rigid, pre-defined sets. By introducing a planning-based framework that accounts for the “hard” constraints—such as kinematic feasibility and motion coherence—Lai’s approach allows robots to dynamically adapt choreography to music in real time, moving closer to human-like improvisation. This contribution has implications for human-robot interaction, entertainment robotics, and creative AI, offering a scalable method for generating fluid, context-aware motion sequences. Though early in their career, Lai’s work signals a shift from reactive to proactive robotic performance, blending computational planning with artistic expression. Their research continues to inspire new directions in autonomous choreography, where robots are not just dancers but co-creators of movement.