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About

Peipei Song’s research lies at the intersection of brain-computer interfaces (BCI), service robotics, and intelligent vision systems, with a focus on enhancing human-robot interaction for assistive applications. Her most cited work, “Design of an SSVEP-based BCI system with visual servo module for a service robot to execute multiple tasks” (2017, 11 citations), demonstrates how steady-state visual evoked potentials can translate human intent into robot commands, enabling physically challenged users to control service robots for daily tasks. Song has also advanced environment perception through dynamic image stitching for moving objects (8 citations) and developed intelligent vision localization systems for obstacle avoidance and grasping in indoor service robots (6 citations). Her research extends to cooperative multi-robot control via BCI with vision-assisted navigation (4 citations) and ceiling feature-based vision control for navigation (2 citations). By integrating BCI with visual servo and navigation modules, Song addresses critical challenges in real-world robot deployment—such as multi-task execution and multi-robot coordination—making her work foundational for accessible, autonomous assistive robotics.