Papers
2
Total Citations
9
H-Index
2
About
Zhen Nie is a robotics researcher whose work bridges the critical gap between perception and manipulation in challenging industrial environments. His primary research areas include 3D LiDAR-based simultaneous localization and mapping (SLAM), point cloud registration, and the design and control of cable-suspended robots for automated material sorting. Nie’s major contributions lie in enhancing the robustness of robotic perception in degraded environments, particularly through his 2023 work on 3D LiDAR point cloud registration using IMU preintegration in coal mine roadways—a method that addresses the challenges of local point cloud sparseness and motion distortion, achieving 6 citations. He has also advanced the field of robotic manipulation with his development of a cable-suspended gangue-sorting robot (CSGSR), where he introduced novel techniques for generating minimum dynamic cable tension workspaces and analyzing cable tension sensitivity, earning 3 citations. This work addresses the practical challenge of separating gangue from coal using robots, tackling the unidirectional nature of cables and dynamic pick-and-place impacts. Nie’s research is notable for its direct application to hazardous underground environments, demonstrating a commitment to deploying robotics solutions where they are most needed.
Research Focus
Key Achievements
Top Papers
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