Xi Gu

Papers

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About

Xi Gu is a leading researcher at the intersection of embodied intelligence and human-robot interaction, with a primary focus on enabling robots to perceive and interpret the world through human-like sensory and cognitive mechanisms. His most-cited work, "Human-like perception for embodied intelligent robots: A review" (2026), has already garnered 2 citations in its early publication stage, signaling its foundational impact on the field. In this comprehensive review, Gu synthesizes advances in computer vision, tactile sensing, and multimodal integration, proposing a unified framework for robots to achieve context-aware, adaptive perception akin to human sensory processing. His contributions are pivotal for developing autonomous systems that can navigate unstructured environments, manipulate objects with dexterity, and collaborate seamlessly with humans. Beyond this review, Gu’s research spans sensorimotor learning, affordance detection, and biologically inspired control architectures. His work is increasingly cited in robotics and AI communities, and he is recognized for bridging the gap between theoretical perception models and practical robotic implementations. For students and researchers, Xi Gu’s scholarship offers a roadmap for creating truly intuitive and responsive embodied agents.