Zhenghui Gu

About

Zhenghui Gu is a leading researcher in brain-computer interfaces (BCI) and intelligent robotic control, with a focus on enhancing human-robot collaboration for assistive technologies. Her major contributions lie in developing advanced shared control frameworks that intelligently balance autonomy and human intent, particularly for brain-actuated wheelchair robots. In her highly cited 2020 paper (67 citations), she proposed a Bayesian shared control approach that optimally combines robot automatic control with brain-machine interface commands, accounting for uncertainty in perception and action. She further advanced this work with a self-adaptive shared control system (31 citations) that uses a brain state evaluation network to dynamically adjust control weights based on operator skill levels. Gu has also demonstrated expertise in high-degree-of-freedom robotic manipulation, developing an SSVEP-based BCI system for controlling a 4-DOF robotic manipulator. Her research directly addresses critical challenges in BCI-based assistive robotics, including uncertainty management and adaptive human-robot cooperation. With her innovative approaches to shared autonomy, Gu is making significant strides toward practical, user-friendly brain-controlled assistive devices that can adapt to individual user capabilities.

Research Focus

Key Achievements

Top Papers

1. 1
   A Bayesian Shared Control Approach for Wheelchair Robot With Brain Machine Interface

   67 citations · 2020
2. 2
   Self-adaptive shared control with brain state evaluation network for human-wheelchair cooperation

   31 citations · 2020
3. 3
   A SSVEP-Based BCI for Controlling a 4-DOF Robotic Manipulator

   3 citations · 2019

Key Collaborators

Contact & Links