Papers
15
Total Citations
514
H-Index
9
About
Xiaodong Zhou is a leading researcher in bio-inspired robotics and rehabilitation engineering, with a focus on compliant legged robots and ankle rehabilitation systems. His work bridges biology and robotics, notably through a highly cited survey on bio-inspired compliant legged robot designs (116 citations), which explores how biological springs enhance robot agility and efficiency over rigid counterparts. Zhou has made significant contributions to medical robotics, developing novel wearable parallel mechanisms and whole-stage compliance training strategies for ankle rehabilitation, as seen in his 2021 systematic review (113 citations) and a 2020 paper on a new ankle robotic system (76 citations). His impact extends to dynamic modeling and control, including a Lie-theory-based methodology for serial manipulators (50 citations) and spatial iterative learning control for robotic path learning (35 citations). Zhou also advances robot learning with work on peg-in-hole assembly using Cartesian DMPs (26 citations) and impedance learning for physical training (14 citations). With over 500 total citations across his top papers, Zhou’s research is pivotal for developing safer, more adaptive robots for rehabilitation and human-robot interaction, making him a key figure in compliant robotics and assistive technology.
Research Focus
Key Achievements
Top Papers
- 1A survey of bio-inspired compliant legged robot designs116 citations · 2012
- 2State of the art in parallel ankle rehabilitation robot: a systematic review113 citations · 2021
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- 6Spatial iterative learning control for robotic path learning35 citations · 2022
- 7Learning peg-in-hole assembly using Cartesian DMPs with feedback mechanism26 citations · 2020
- 8Impact modelling and analysis of the compliant legged robots23 citations · 2012
- 9Robotic Impedance Learning for Robot-Assisted Physical Training14 citations · 2019
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