Junyuan Deng

Papers

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About

Junyuan Deng is a robotics researcher whose work focuses on advancing visual-inertial odometry (VIO) for robust pose estimation in complex environments. His key contribution lies in pioneering VIO algorithms tailored for 360° cameras, leveraging their wide field of view to overcome the limitations of traditional narrow-lens systems. His most-cited paper, "360-VIO: A Robust Visual–Inertial Odometry Using a 360° Camera" (2023), has already garnered 19 citations, reflecting its early impact on the field. This work addresses a critical challenge in industrial robotics—maintaining accurate localization in dynamic or feature-sparse settings—by exploiting omnidirectional visual data. Deng’s research bridges the gap between hardware innovation and algorithmic design, offering practical solutions for autonomous navigation in manufacturing, inspection, and logistics. His achievements demonstrate a keen ability to identify underutilized sensor modalities and translate them into reliable, real-world systems. As the demand for resilient robot perception grows, Deng’s contributions position him as a rising voice in the VIO community, with potential to shape future standards for wide-angle sensing in robotics.