Papers
2
Total Citations
6
H-Index
1
About
Haoze Zhuo is a rising researcher at the intersection of biomimetic perception and aerial robotics. His work focuses on two key frontiers: geometric-semantic scene understanding for autonomous navigation, and reinforcement learning for airborne robotic arm control. In his most cited paper, "Perceiving like a Bat" (2023, 5 citations), Zhuo introduces a hierarchical 3D perception framework inspired by echolocation, enabling robots to interpret complex, time-varying natural scenes despite sensor limitations—a critical step toward spatial intelligence that rivals biological systems. This biomimetic approach addresses a fundamental challenge in robotics: robust scene understanding under real-world constraints. More recently, in "Encouraging Guidance" (2025, 1 citation), Zhuo pioneers a reinforcement learning method for floating target tracking with airborne robotic arms, improving learning efficiency and control flexibility for aerial contact operations. While early in his career, Zhuo’s work demonstrates a clear trajectory toward integrating biological inspiration with practical robotic control. His research holds promise for applications in search-and-rescue, environmental monitoring, and autonomous manipulation in unstructured environments, marking him as a researcher to watch in the field of intelligent robotics.
Research Focus
Key Achievements
Top Papers
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