Max Robotics — Global Service Robot Directory + US Certification

About

Pengcheng Wen is a pioneering researcher at the intersection of brain-machine interfaces (BMIs), human-robot interaction, and assistive robotics technology. His work focuses primarily on developing innovative control systems that enable individuals with paralysis or limited mobility to interact with robotic systems through non-muscular interfaces, combining gaze-tracking, electroencephalography (EEG)-based brain signals, and augmented reality feedback. Wen's most influential contribution, "Closed-Loop Hybrid Gaze Brain-Machine Interface Based Robotic Arm Control with Augmented Reality Feedback" (2017, 72 citations), demonstrated a sophisticated closed-loop system enabling paralyzed individuals to grasp and manipulate objects with unprecedented efficiency. Building on this foundation, his subsequent work on semi-autonomous robotic arm reaching (2020, 35 citations) advanced shared control strategies that blend user intent with intelligent automation, significantly reducing the cognitive burden on BMI users. His research extends beyond individual assistance to multi-robot systems, exploring how hybrid gaze-BCI interfaces can manage complex scenarios where operators' hands are otherwise occupied. Additionally, his investigations into affordable eye-tracking solutions demonstrate a commitment to accessibility and real-world applicability. Collectively accumulating over 140 citations, Wen's body of work represents meaningful progress toward practical, user-centered assistive technologies for individuals with severe motor impairments.