Papers
2
Total Citations
175
H-Index
2
About
Pengfei Chen’s research lies at the dynamic intersection of agricultural robotics, brain–computer interfaces (BCIs), and intelligent control systems. His work is distinguished by a rare ability to merge computer vision with real-world, open-field applications—as demonstrated in his highly cited 2021 study on mango picking, which achieved 88 citations for its novel use of instance segmentation and key point detection from RGB images. This approach enables precise fruit localization in unstructured orchard environments, directly addressing a critical bottleneck in automated harvesting. Equally impactful is his pioneering development of an adaptive asynchronous control system for robotic arms, powered by an augmented reality-assisted BCI (87 citations). By integrating brain signals with AR feedback, Chen’s system dramatically improves the flexibility and responsiveness of brain-controlled prosthetics, overcoming long-standing limitations in human–robot interaction. Together, these contributions showcase his talent for translating complex algorithms into practical, high-impact solutions. With over 175 citations across his most-cited works, Chen is a rising figure in intelligent robotics, whose research continues to push the boundaries of how machines perceive, adapt to, and assist in the physical world.
Research Focus
Key Achievements
Top Papers
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