Shengjie Jiao

Chang'an University

Papers

3

Total Citations

20

H-Index

2

About

Shengjie Jiao is pioneering the automation of road safety with cutting-edge research on traffic cone robots (TCRs)—autonomous systems designed to enhance construction zone safety and traffic flow. His work centers on robust formation tracking control, tackling the complex challenge of enabling swarms of TCRs to move cohesively while navigating real-world environmental constraints and uncertain disturbances. Jiao’s most influential paper, "Optimization of robust formation tracking control for traffic cone robots with matching and mismatching uncertainties: A fuzzy-set theory-based approach" (2023), has garnered 14 citations for its novel fuzzy-set framework that handles both matched and mismatched uncertainties. He further advanced the field with "Formation Tracking Control of the Traffic Cone Robots System Under the Environmental Constraints" (2024, 4 citations), introducing a feedforward-based controller that allows TCRs to perform swarm behaviors and track fixed targets despite environmental limitations. His latest work (2025) addresses adaptive robust control under leakage and dead-zone-type disturbances, pushing the boundaries of reliability. With a focused trajectory and growing citation impact, Jiao is establishing himself as a key contributor to intelligent transportation and robotic swarm control.

Research Focus

Key Achievements

2
H-Index
3
Papers
20
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Optimization of robust formation tracking control for traffic cone robots with matching and mismatching uncertainties: A fuzzy-set theory-based approach
14 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Chang'an University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago