Yifan Yin

Papers

Total Citations

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About

Yifan Yin is a robotics researcher whose work centers on advancing haptic perception and multimodal sensing for robotic systems. His primary contributions lie in developing novel tactile sensors that expand the capabilities of robots to interact with and understand their environments. Yin’s most cited paper, “FVSight: A Novel Multimodal Tactile Sensor for Robotic Object Perception” (2022), addresses a critical limitation in existing haptic sensors: their restricted sensing area and single-modality data collection. By proposing a sensor that integrates multiple tactile modalities over a broader surface, Yin enables robots to perceive objects more comprehensively, moving beyond fingertip-only sensing. This innovation has garnered 3 citations, reflecting its early but promising impact on the field. Yin’s work is particularly notable for its potential to enhance robotic dexterity in unstructured settings, such as manufacturing or search-and-rescue operations. His research bridges hardware design and perception algorithms, offering a foundation for future studies in tactile-driven robotic manipulation. For students and researchers, Yin’s contributions underscore the importance of multimodal sensing in achieving more human-like robotic interaction.