Shujie Ji
Papers
1
Total Citations
2
H-Index
1
About
Shujie Ji is a robotics researcher whose work focuses on the intersection of reinforcement learning and legged locomotion, particularly for hexapod robots operating in challenging environments. Ji’s most notable contribution is the development of a layered modular motion control framework that integrates reinforcement learning with foot impedance control and an optimized reward mechanism. This approach, detailed in the 2024 paper "Optimization Control of Attitude Stability for Hexapod Robots Based on Reinforcement Learning," directly addresses the critical challenge of maintaining attitude stability on rough terrain. By combining gait planning with adaptive foot impedance coordination, Ji’s method enables hexapod robots to dynamically adjust their posture and force distribution, significantly improving their robustness and stability during traversal of uneven surfaces. This work, with 2 citations to date, represents an early but promising step toward more autonomous and resilient multi-legged robots. Ji’s research is particularly relevant for applications in search-and-rescue, planetary exploration, and industrial inspection, where reliable locomotion over unpredictable terrain is essential.
Research Focus
Key Achievements
Top Papers
- 1