Ziyang Meng

Papers

Total Citations

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About

Ziyang Meng is a rising researcher in the field of embodied AI and autonomous navigation, with a focus on integrating visual perception with goal-oriented robotic control. His most-cited work, "VF-Nav: Visual Floor-Plan-Based Point-Goal Navigation" (2025), introduces a novel framework that leverages floor-plan representations to enhance a robot’s ability to navigate complex indoor environments using only visual inputs. This contribution addresses a critical challenge in robotics—bridging the gap between high-level spatial understanding and low-level motion planning—by enabling agents to interpret and act upon topological maps derived from real-world scenes. While his citation count is still growing, Meng’s work is notable for its practical approach to point-goal navigation, a core problem in service robotics and autonomous systems. His research promises to improve the efficiency and reliability of robots in human-centric spaces, from homes to warehouses. As an early-career scholar, Meng’s innovative use of visual floor plans marks him as a promising voice in the intersection of computer vision and robotics, with potential for significant future impact as his methods gain wider adoption.