Van-Long Trinh

Hanoi University of Industry

Papers

3

Total Citations

36

H-Index

2

About

Dr. Van-Long Trinh is a rising scholar at the intersection of intelligent robotics, multi-criteria decision-making, and advanced energy harvesting technologies. His work is defined by a practical, systems-level approach to solving complex engineering challenges. Dr. Trinh’s most impactful contribution, with 33 citations, is his development of an integrated Fuzzy AHP-TOPSIS framework for industrial robot selection, providing manufacturers with a robust, data-driven tool to optimize productivity and safety. In autonomous robotics, he has advanced real-time navigation by enhancing the Rapidly-exploring Random Tree (RRT) algorithm for dynamic obstacle avoidance in unstructured indoor environments, a critical step toward more resilient mobile robots. Demonstrating remarkable breadth, Dr. Trinh has also contributed a comprehensive review on advanced triboelectric nanogenerators, exploring their potential to power the next generation of smart devices and healthcare monitors. This work signals his growing interest in sustainable, self-powered systems. While early in his career, the immediate citation of his decision-making model underscores its practical value to industry. Dr. Trinh’s research portfolio—spanning from factory floor optimization to autonomous navigation and green energy—positions him as a versatile and forward-thinking engineer whose work directly addresses the challenges of modern automation and smart technology.

Research Focus

Key Achievements

2
H-Index
3
Papers
36
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
An Integrated Approach of Fuzzy AHP-TOPSIS for Multi-Criteria Decision-Making in Industrial Robot Selection
33 citations · 2024
📈 Most Prolific Year: 2025 (2 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Hanoi University of Industry

Top Papers

  1. 1
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  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago