Papers
2
Total Citations
42
H-Index
2
About
Yitao Shen is a pioneering researcher at the intersection of human-robot interaction, assistive robotics, and brain-machine interfaces. His work focuses on developing non-muscular control systems that enable individuals with severe motor impairments to operate robotic arms and multi-robot systems using hybrid gaze and brain-computer interfaces (BCI). Shen’s major contributions include the design of shared control strategies that allow users to issue both discrete and continuous commands through eye tracking and neural signals, significantly expanding the autonomy of assistive devices. His most cited paper, "Semi-Autonomous Robotic Arm Reaching With Hybrid Gaze–Brain Machine Interface" (2020), has garnered 35 citations and demonstrates a novel approach to robotic arm control for users with no residual upper limb movement. In his 2023 work, "Extended Control With Hybrid Gaze-BCI for Multi-Robot System Under Hands-Occupied Dual-Tasking," Shen addresses the critical need for hands-free control in complex, real-world multi-robot missions, achieving 7 citations. His research not only advances assistive technology but also lays groundwork for intuitive human-robot collaboration in demanding environments.
Research Focus
Key Achievements
Top Papers
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