Tiandong Zhang
Papers
6
Total Citations
88
H-Index
4
About
Tiandong Zhang is a leading researcher in bionic underwater robotics, with a focus on motion control, autonomous skill learning, and perception for bio-inspired aquatic robots. His major contributions include developing real-time trajectory planning and tracking control for bionic robots in dynamic environments—a work that has garnered 47 citations—and pioneering residual reinforcement learning for the motion control of the bionic exploration robot RoboDact. Zhang also advanced autonomous skill acquisition through curriculum learning, enabling a robotic fish to head a water polo ball in highly dynamic aquatic settings. His innovative work on FlowSight, a vision-based artificial lateral line sensor, enhances underwater flow perception without external instrumentation, while his TacFlex framework simulates multimodal tactile imprints for visuotactile sensors. Most recently, Zhang explored energy-efficient swimming gaits for robotic fish using deep reinforcement learning, revealing the potential of intermittent swimming to conserve energy. With over 88 total citations across his top papers, Zhang’s research bridges reinforcement learning, sensor design, and bio-inspired locomotion, making significant strides toward more capable and efficient autonomous underwater robots.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6