About

Qunhong Tian is a leading researcher in the field of bionic robotics, specializing in the design, control, and path planning of autonomous underwater vehicles (AUVs), particularly bionic robotic fish. Tian’s work addresses critical challenges in underwater navigation by developing advanced optimization algorithms that enable robotic fish to operate efficiently in complex, three-dimensional environments with unpredictable ocean currents and moving obstacles. A key contribution is the introduction of a two-level optimization algorithm for path planning, which has garnered 26 citations, and the use of robust optimization methods to handle uncertain currents (10 citations). Tian has also advanced the mechanical design of these robots, optimizing multi-fin propulsion systems to balance low-speed maneuverability with high-speed stability—a breakthrough highlighted in a widely cited review (23 citations). By integrating deep reinforcement learning, such as an improved deep Q-network, Tian continues to push the boundaries of autonomous underwater exploration. With over 64 total citations, Tian’s work is foundational for applications in environmental monitoring, archaeology, and infrastructure inspection, establishing them as a key innovator in bionic underwater robotics.

Research Focus

Key Achievements

3
H-Index
5
Papers
64
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
A two-level optimization algorithm for path planning of bionic robotic fish in the three-dimensional environment with ocean currents and moving obstacles
26 citations · 2022
📈 Most Prolific Year: 2022 (4 Papers)
🤝 Key Collaborators: 19
🏛 Institutions: China University of Petroleum, East China, Shandong University of Science and Technology, Qingdao University of Science and Technology, Harbin Engineering University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago