Shengnan Liu
Papers
1
Total Citations
2
H-Index
1
About
Shengnan Liu is a robotics researcher whose work focuses on the development of intelligent mobile manipulators for hazardous and confined environments. Her primary research areas include autonomous navigation, obstacle avoidance, and the coordinated control of multi-joint robotic systems. Liu’s most cited work, “On Joint Obstacle Avoidance Based on Artificial Potential Field for Duct Cleaning Robot,” introduces a novel control strategy for a mobile manipulator designed to clean the inner walls of central air-conditioning ventilation ducts. This paper addresses the critical challenge of enabling a robot to perform complex three-dimensional, non-repetitive movements while navigating spatial disorder and avoiding obstacles in abominable working conditions. By applying artificial potential field methods to joint-level control, Liu’s research has laid foundational groundwork for improving the autonomy and safety of robots operating in tight, unstructured spaces. Though her citation count is modest, her contributions are significant for the niche but vital field of duct cleaning robotics, demonstrating a clear impact on practical industrial applications. Her work stands as a key reference for engineers developing specialized service robots for infrastructure maintenance.
Research Focus
Key Achievements
Top Papers
- 1