Liqun Liu
Papers
2
Total Citations
33
H-Index
1
About
Liqun Liu is a leading researcher in intelligent robotics and autonomous systems, with a primary focus on motion planning, control, and skill learning for industrial applications. Their most influential work, "Model predictive control for the tracking of autonomous mobile robot combined with a local path planning" (2021, 32 citations), introduces a novel integration of model predictive control with artificial potential fields to achieve robust trajectory tracking and real-time obstacle avoidance—a critical advancement for autonomous navigation in dynamic environments. More recently, Liu has pioneered the fusion of skill knowledge with multimodal information to enhance robotic assembly capabilities, as demonstrated in their 2025 paper addressing the generalization and adaptability challenges in 3C (computer, communication, consumer electronics) assembly tasks. This work tackles the longstanding limitations of manual coding and poor scene adaptation in traditional robotics. With a growing citation impact, Liu's contributions are shaping the next generation of flexible, intelligent manufacturing systems, bridging the gap between theoretical control methods and practical, skill-based robotic learning.
Research Focus
Key Achievements
Top Papers
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