Papers
8
Total Citations
126
H-Index
6
About
Yongxuan Wang is a leading researcher at the intersection of brain-computer interfaces (BCIs), shared autonomous control, and neuromuscular robotics. His work focuses on enabling more intuitive and reliable human-robot interaction, particularly for assistive and musculoskeletal systems. Wang’s most impactful contribution is his 2015 paper on an FDES-based shared controller for asynchronous brain-actuated robots (55 citations), which pioneered a method to overcome the low channel capacity and high error rates of BCIs by blending human intent with autonomous robotic assistance. He further advanced this concept with fuzzy-based shared controllers (2011) and mobile robot navigation systems (2014). In neuromuscular robotics, Wang has made significant strides with his 2023 work on Proximal Policy Optimization with time-varying muscle synergy for upper limb control (21 citations) and a 2024 computational method to identify optimal functional muscle synergies (6 citations). His earlier work on azimuthal source localization using interaural coherence in a robotic dog (22 citations) and auditory feedback for teleoperated navigation (2011) demonstrates his versatility in multi-modal sensing and control. Wang’s research has accumulated over 126 citations, with his bionic cerebellar controller for humanoid robots (2022) representing a promising new direction in bio-inspired locomotion.
Research Focus
Key Achievements
Top Papers
- 1An FDES-Based Shared Control Method for Asynchronous Brain-Actuated Robot55 citations · 2015
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- 4A fuzzy-based shared controller for brain-actuated simulated robotic system10 citations · 2011
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