Papers
10
Total Citations
94
H-Index
6
About
Tianze Hao is an emerging robotics researcher whose work centers on soft robotic hands, anthropomorphic gripper design, and intelligent soft robotics systems. His research addresses one of the field's central challenges: creating robotic hands that combine the safety and adaptability of soft materials with the dexterity and functionality of the human hand. His most cited work, "Multijointed Pneumatic Soft Hand with Flexible Thenar" (2021, 27 citations), pioneered a multijointed pneumatic architecture that closely mimics human hand kinematics, while his 2024 review on anthropomorphic soft hands surveys the broader landscape of dexterity, sensing, and machine learning integration in the field. Notably, Hao has made distinctive contributions through his fingerprint-inspired surface texture research, demonstrating how biologically derived surface patterns significantly enhance grip performance under lubricated and slippery conditions — a thread running through multiple publications. His work on the Dexterous All-Soft Hand (DASH) further expanded the field by addressing active palm motion, an often-overlooked element of hand dexterity. With over 90 cumulative citations across ten publications, Hao's research meaningfully advances the design and intelligence of next-generation soft robotic systems with real-world applications in healthcare, services, and beyond.
Research Focus
Key Achievements
Top Papers
- 1Multijointed Pneumatic Soft Hand with Flexible Thenar27 citations · 2021
- 2Anthropomorphic Soft Hand: Dexterity, Sensing, and Machine Learning15 citations · 2024
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- 5Integrated and Intelligent Soft Robots11 citations · 2023
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- 8Flexible soft Pneumatic Bionic Hand Based on Multi-Jointed Structure2 citations · 2023
- 9Algorithm Research Based on an Elliptical Arc Fitting Curve1 citations · 2024
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