Mengyuan Gu

Tsinghua University, Hefei University of Technology

Papers

Total Citations

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About

Mengyuan Gu is a robotics researcher whose work focuses on enabling autonomous mobile robots to navigate safely and efficiently in real-world environments. Her primary research areas include simultaneous localization and mapping (SLAM) and dynamic obstacle avoidance, with a particular emphasis on hardware-accelerated, onboard solutions. In her highly cited 2015 paper, Gu presented an FPGA-based real-time SLAM system that addresses the critical challenge of limited payload and power on mobile robots, demonstrating the feasibility of recovering indoor trajectories directly on the robot. This work, with 16 citations, has been influential in advancing embedded SLAM solutions. More recently, her 2021 study on dynamic obstacle avoidance introduced an adaptive velocity obstacle method that overcomes the limitations of traditional approaches by intelligently navigating the boundary between collision and non-collision velocity zones. Garnering 11 citations, this contribution is vital for safe robot navigation in cluttered, dynamic settings. Gu’s research bridges the gap between theoretical algorithms and practical, resource-constrained deployment, making her work essential reading for students and engineers developing next-generation autonomous systems.