Entong Su
Papers
4
Total Citations
52
H-Index
3
About
Entong Su is a robotics researcher whose work centers on the challenging intersection of deformable object manipulation, tactile sensing, and simulation-based control. His primary contributions lie in advancing robotic manipulation of rope-like objects—a critical capability for applications such as autonomous surgical suturing. Su pioneered the use of differentiable compliant position-based dynamics to model and control deformable ropes, enabling robots to plan and execute complex manipulations with unprecedented accuracy. His 2023 paper on this topic has garnered 42 citations, reflecting its impact on the field. Su has also tackled the notoriously difficult problem of tactile-based manipulation, proposing reinforcement learning frameworks that allow robots to generalize manipulation skills to unseen, diverse objects. Additionally, his work on parameter identification and motion control for articulated robots using differentiable dynamics has strengthened the bridge between simulation and real-world performance. Through these contributions, Su is helping to make model-based control more robust and transferable, pushing the boundaries of what robots can achieve with soft, deformable, and unfamiliar objects.
Research Focus
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Top Papers
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