Papers

4

Total Citations

30

H-Index

3

About

Guirong Han is a leading researcher in industrial robotics, with a focused expertise in energy-efficient trajectory planning and welding automation. Their work addresses the critical challenge of reducing energy consumption in industrial robots, which are widely used but often operate with low efficiency. Han’s major contributions include developing an improved sparrow search algorithm for optimal trajectory planning, which minimizes robot energy consumption while ensuring smooth joint coordination—a method detailed in their most-cited paper (2024, 16 citations). They have also advanced energy consumption modeling through system decomposition of welding robots (2023, 7 citations) and proposed a hierarchical approach to optimize energy use across robotic systems (2025, 4 citations). In the domain of welding, Han pioneered dual robot coordinated trajectory planning for complex weld seams, such as single Y-groove joints in plug-in cross pipes (2020, 3 citations), enhancing automation in saddle-shaped space curve welding. With a cumulative impact of over 30 citations, Han’s work is pivotal for sustainable manufacturing, offering practical solutions to reduce operational costs and environmental footprint in robotic welding processes.

Research Focus

Key Achievements

3
H-Index
4
Papers
30
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Optimal trajectory planning of robot energy consumption based on improved sparrow search algorithm
16 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Hubei Institute of Fine Arts, Wuhan Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago