Aiwen Luo
Papers
9
Total Citations
165
H-Index
5
About
Aiwen Luo is a researcher whose work bridges the critical intersection of computer vision and robotics, with a primary focus on real-time semantic segmentation and bipedal robot locomotion. Luo's most significant contribution is the development of LMFFNet, a well-balanced lightweight network for fast and accurate semantic segmentation, which has garnered 104 citations for its ability to maintain high accuracy while dramatically reducing computational complexity—a crucial advancement for autonomous driving and robotics. In the domain of humanoid robotics, Luo has pioneered the use of force sensors for surface-property recognition, enabling stable walking on diverse terrains. This body of work, spanning multiple papers with 14 citations each, introduces innovative methods for surface identification through walking-pattern classification and force-sensory data analysis, allowing robots to dynamically adjust their walking speed and energy efficiency. Luo's research is particularly notable for its hardware-aware approach, including a dual-feature-based object recognition coprocessor, and for addressing practical challenges in real-world robot deployment. Through these contributions, Luo has established a reputation for creating computationally efficient solutions that enhance robot autonomy and safety in complex human environments.
Research Focus
Key Achievements
Top Papers
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- 7Force-Sensor-Based Walking-Environment Recognition of Biped Robots2 citations · 2020
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