Papers
9
Total Citations
145
H-Index
6
About
Ru Tong is a leading researcher in bioinspired underwater robotics, specializing in the design, optimization, and control of high-performance robotic fish and dolphins. Their major contributions include the development of an untethered robotic tuna that achieves both high swimming speed and steering maneuverability through mechanism optimization and novel steering strategies, as well as the creation of a bionic tensegrity robotic fish with a continuum body that replicates the flexibility of biological fish. Tong has also pioneered active variable stiffness control for robotic dolphins, enabling dynamic body stiffness modulation to improve swimming performance under varying conditions. With over 145 citations across their most-cited works, Tong’s research has significantly advanced the field of bionic underwater robots. Notable achievements include the design of an integral molding flexible tail for robotic fish, a robust CPG-based rhythm generator for robot motion control, and a fish-like binocular vision system for underwater perception. Their work on reinforcement learning methods for bionic underwater robots has opened new avenues for intelligent motion control and decision-making, making Tong a key figure in the evolution of autonomous underwater vehicles.
Research Focus
Key Achievements
Top Papers
- 1Design and Optimization of an Untethered High-Performance Robotic Tuna50 citations · 2022
- 2A Survey on Reinforcement Learning Methods in Bionic Underwater Robots34 citations · 2023
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- 5Design and Modeling of an Integral Molding Flexible Tail for Robotic Fish10 citations · 2024
- 6NA-CPG: A robust and stable rhythm generator for robot motion control8 citations · 2022
- 7Online Optimization of Normalized CPGs for a Multi-Joint Robotic Fish6 citations · 2021
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- 9Vertical-Plane Locomotion Control of a High-Speed Robotic Tuna via NMPC1 citations · 2025