Papers
3
Total Citations
34
H-Index
3
About
Yaru Liu is a pioneering researcher at the intersection of brain-computer interfaces (BCIs) and multi-robot systems (MRSs), with a core focus on shared control frameworks that enable seamless human-multirobot cooperation. Her major contributions lie in developing innovative strategies to overcome the inherent limitations of autonomous MRSs—such as sensor errors, communication delays, and environmental uncertainties—by integrating human cognitive input through non-invasive BCIs. In her most-cited work (2021, 16 citations), she introduced a shared control paradigm that allows a single operator to collaboratively guide multiple robots in complex tasks, effectively blending human intuition with robotic precision. Her subsequent paper on human-multirobot foraging (2021, 11 citations) extended this framework to real-world applications like search-and-rescue, demonstrating how BCIs can enhance strategic consensus in dynamic environments. Additionally, her 2020 study on differential world models (7 citations) advanced the field by enabling robots to predict and adapt to operator intent. With a growing citation impact, Liu’s work is notable for bridging neuroscience and robotics, offering scalable solutions for human-robot teams in hazardous or inaccessible settings—a critical step toward intuitive, brain-driven automation.
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