Papers
1
Total Citations
5
H-Index
1
About
Fei Zheng is a pioneering researcher in the field of robotic perception and edge computing, with a primary focus on acoustic simultaneous localization and mapping (SLAM) systems. His most notable contribution is the development of a graph optimization-based acoustic SLAM edge computing framework that achieves centimeter-level mapping accuracy while incorporating reflector recognition capabilities. This breakthrough addresses a critical challenge in robotics: enabling autonomous navigation in environments where visual sensors fail, such as dark or smoke-filled spaces. By leveraging echo signals and time-of-arrival (TOA) data from room impulse responses (RIR), Zheng’s system allows robots to map unknown environments without relying on cameras. His work has garnered significant attention, with his 2021 paper on this topic accumulating 5 citations, reflecting its emerging impact in the field. Zheng’s research bridges the gap between acoustic signal processing and practical robotic applications, offering a robust solution for disaster response, underground exploration, and industrial automation. His achievements highlight a commitment to advancing edge computing technologies that enhance robot autonomy in challenging conditions.
Research Focus
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Top Papers
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