Yating Lin
Papers
1
Total Citations
9
H-Index
1
About
Yating Lin is a rising researcher in robot manipulation, with a focus on articulated and deformable objects—systems that are inherently compliant and under-actuated. Her key research areas include model-predictive control (MPC), subgoal generation, and coarse-to-fine planning for robotic motion. Lin’s major contribution is the development of “Subgoal Diffuser,” a novel framework that uses coarse-to-fine subgoal generation to guide MPC for complex manipulation tasks. This approach addresses the challenge of unexpected disturbances that cause objects to deviate from predicted states, enabling more robust and adaptive robot control. Her work has already garnered attention, with her 2024 paper earning 9 citations shortly after publication—a strong indicator of its early impact in the field. By bridging the gap between high-level planning and low-level control, Lin’s research offers practical solutions for real-world manipulation scenarios, such as handling soft or jointed objects. Her innovative integration of diffusion models with MPC marks a notable achievement, positioning her as a promising contributor to advancing autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
- 1