Zonghao Huang
Papers
1
Total Citations
50
H-Index
1
About
Zonghao Huang is a robotics researcher whose work focuses on advancing how robots perceive and interact with their environments through continuous, probabilistic mapping. His key research areas include spatial perception, Gaussian Process Implicit Surfaces (GPISs), and online mapping for autonomous systems. Huang’s major contribution lies in developing an online continuous mapping approach using GPISs, which allows robots to represent environments more efficiently than traditional grid-based methods. By better utilizing sparse sensor measurements, his method enables robots to build smooth, probabilistic maps in real time—critical for navigation and manipulation in unstructured settings. His most-cited paper, "Online Continuous Mapping using Gaussian Process Implicit Surfaces" (2019), has garnered 50 citations, reflecting its impact on the robotics community. This work is notable for addressing a fundamental challenge in robotics: balancing computational efficiency with representational fidelity. Huang’s research bridges the gap between theoretical probabilistic modeling and practical robotic deployment, making him a rising contributor to the field of autonomous perception and mapping.
Research Focus
Key Achievements
Top Papers
- 1Online Continuous Mapping using Gaussian Process Implicit Surfaces50 citations · 2019