Fengmao Lv
Papers
2
Total Citations
12
H-Index
2
About
Fengmao Lv is at the forefront of intelligent robotics, specializing in multi-robot systems, semantic navigation, and visual-language alignment. His research addresses a fundamental challenge in service robotics: how multiple robots can cooperatively explore unfamiliar environments by leveraging semantic knowledge and human-like reasoning. In his highly cited 2024 work, "VLAI," Lv pioneered a visual-language aligned information framework that enables robots to balance exploration and exploitation during object goal navigation, achieving more efficient decision-making in complex household settings. Building on this, his 2025 paper on "Enhancing Multi-Robot Semantic Navigation Through Multimodal Chain-of-Thought Score Collaboration" introduced a novel approach that models how humans cooperatively use semantic knowledge to determine navigation directions—a significant departure from previous single-robot centralized planning strategies. With papers already garnering 6 citations each shortly after publication, Lv's work is rapidly shaping the next generation of house service multi-robot systems. His research promises to make domestic robots more intuitive and collaborative, bringing us closer to truly intelligent home assistants that can work together seamlessly.
Research Focus
Key Achievements
Top Papers
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- 2