Papers
1
Total Citations
24
H-Index
1
About
He Yin is an emerging robotics researcher whose work sits at the cutting edge of autonomous systems, intelligent control, and underwater robotics. His most notable contribution centers on the development of a decentralized hierarchical deep reinforcement learning-based motion control strategy for multiple amphibious spherical robots (ASRs) equipped with tilting thrusters — a landmark 2023 study that has already garnered 24 citations, reflecting rapid recognition within the field. This work directly addresses one of the most persistent challenges in underwater robotics: enabling reliable, adaptive motion control in unknown and hostile environments. By leveraging deep reinforcement learning in a decentralized framework, Yin's approach allows multiple robotic agents to coordinate autonomously without relying on centralized computation, significantly advancing the scalability and resilience of multi-robot underwater systems. His research bridges the gap between theoretical reinforcement learning and real-world deployment of amphibious platforms, pushing the boundaries of what autonomous underwater vehicles can achieve in unstructured settings. For students and researchers in robotics, autonomous control, or marine technology, Yin's work represents an important and timely contribution to the growing field of intelligent multi-agent robotic systems.
Research Focus
Key Achievements
Top Papers
- 1