Papers

17

Total Citations

621

H-Index

11

About

Weijia Tao is a leading researcher in soft robotics, specializing in the sensing, control, and actuation of compliant systems for safe human-robot interaction. His work addresses fundamental challenges in making soft robots precise and autonomous, with major contributions to proprioceptive curvature sensing and sliding-mode control of soft bending modules—a paper that has garnered 144 citations. Tao pioneered the development of a self-contained soft robotic snake platform with integrated curvature sensing (72 citations), advancing the field’s ability to achieve autonomous locomotion in unstructured environments. He also introduced feedforward augmented sliding-mode control for antagonistic soft pneumatic actuators (70 citations), enabling inexpensive, reliable muscle-like actuation. His research extends to wearable soft robotics for human assistance and augmentation, as highlighted in a 2021 literature review. With over 580 total citations across his most-cited works, Tao’s innovations in modular soft manipulators, adaptive control, and origami-inspired kinematic design have significantly impacted the trajectory of soft robotics, offering practical solutions for inspection, search-and-rescue, and collaborative robotics.

Research Focus

Key Achievements

11
H-Index
17
Papers
621
Total Citations
37
Avg Citations/Paper
🏆 Most Cited Paper
Toward Modular Soft Robotics: Proprioceptive Curvature Sensing and Sliding-Mode Control of Soft Bidirectional Bending Modules
144 citations · 2017
📈 Most Prolific Year: 2015 (5 Papers)
🤝 Key Collaborators: 25
🏛 Institutions: Worcester Polytechnic Institute, Arizona State University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago