Papers
3
Total Citations
16
H-Index
2
About
Donghao Shi is a robotics researcher focused on advancing dual-arm robotic manipulation through learning from demonstration and dynamic movement primitives (DMPs). His work centers on enabling robots to perform complex, coordinated tasks—particularly with deformable objects—by learning directly from human demonstrations. Shi’s most cited paper, "DMPs-based skill learning for redundant dual-arm robotic synchronized cooperative manipulation" (2021, 11 citations), establishes a foundational framework for synchronized bimanual control. He further extends this line of research in "A Learning System for Deformable Object Cooperative Manipulation" (2024, 3 citations), addressing the challenging problem of handling non-rigid materials, and in "A constrained framework based on IBLF for robot learning with human supervision" (2023, 2 citations), which integrates human oversight to ensure safe and constraint-aware skill acquisition. By combining DMPs with human-in-the-loop supervision, Shi’s contributions are paving the way for more adaptable and reliable robotic systems in industrial, medical, and domestic applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2A Learning System for Deformable Object Cooperative Manipulation3 citations · 2024
- 3