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About

Pengfei Gu is a robotics researcher whose work centers on autonomous navigation and localization, particularly in GPS-denied and visually challenging environments. His most significant contributions lie in the development of robust visual-inertial odometry (VIO) systems. His highly cited paper, "RVIO: An Effective Localization Algorithm for Range-Aided Visual-Inertial Odometry System" (2023, 13 citations), introduces a novel approach that integrates ultra-wideband (UWB) measurements to dramatically reduce long-term drift in traditional VIO systems, a critical advancement for reliable robot positioning. Gu also pioneered real-time, resource-efficient VIO by implementing a Harris corner detection accelerator on FPGA platforms (2022, 9 citations), enabling high-performance localization on embedded hardware. Extending into navigation, his recent works, "VF-Nav" and "EffoNAV" (both 2025), explore foundation-model-based and floor-plan-guided visual navigation for point-goal and image-goal tasks. By tackling the fundamental challenges of drift, computational efficiency, and robust perception, Gu’s research directly advances the practical deployment of autonomous systems in real-world, infrastructure-free settings, making him a key contributor to modern robotics localization.