Zenan Song

Shanghai Jiao Tong University

Papers

4

Total Citations

53

H-Index

3

About

Zenan Song is an emerging robotics researcher specializing in the design, modeling, and optimization of soft robotic systems, with a particular focus on pneumatic actuation and compliant mechanisms. His work addresses fundamental challenges in how soft robots achieve complex, purposeful motion from simple inputs — a problem with profound implications for automation, manufacturing, and human-robot interaction. Song's most influential contribution, "Morphological Design for Pneumatic Soft Actuators and Robots With Desired Deformation Behavior" (2023, 35 citations), demonstrates how carefully engineered structural geometry can program intricate output motions from a single pressure source, eliminating the need for complex control architectures. This insight represents a significant paradigm shift in soft robot design philosophy. Complementing this, his work on topology optimization for anisotropic stiffness in soft joints (10 citations) bridges compliant mechanism theory with soft actuation, enabling more precise and functional robot joints. His more recent contributions explore dual-mode soft grippers for confined-space grasping and differentiable kinematic modeling using Absolute Nodal Coordinate Formulation (ANCF), advancing both hardware design and computational tools for soft robotic systems. Collectively, Song's research is shaping a more principled, mathematically grounded approach to soft robot engineering.

Research Focus

Key Achievements

3
H-Index
4
Papers
53
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
Morphological Design for Pneumatic Soft Actuators and Robots With Desired Deformation Behavior
35 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Shanghai Jiao Tong University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago