Bowen Liang
Papers
3
Total Citations
6
H-Index
2
About
Bowen Liang is a robotics researcher specializing in state estimation for autonomous mobile robots, particularly in visually degraded and geometrically degenerate environments. His work addresses critical challenges in robot perception and localization, with a focus on firefighting and rescue applications. Liang’s major contributions include developing a generalized differentiable Perspective-n-Point (PnP) method that solves the blind PnP problem without requiring 2D-3D correspondences, enabling accurate pose measurement even with extensive search spaces and outliers. He has also advanced robust odometry for wheeled robots in smoky conditions by integrating smoke-adaptive image features with multisensor tight coupling of visual, inertial, and wheel encoder data. Additionally, Liang’s research on harnessing ground manifold and motion states has improved state estimation in environments where traditional methods fail due to visual occlusion, lidar degradation, or GNSS signal interference. Though his papers are recent (2024–2025), each has already garnered 2 citations, signaling early impact in the field. Liang’s work is notable for its practical focus on enabling autonomous mobility in hazardous conditions, making him a rising contributor to robust robot navigation.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3