Papers
1
Total Citations
9
H-Index
1
About
Hongrui Liu is a robotics researcher whose work focuses on enabling robots to operate effectively in unstructured, everyday environments. His key research areas include robotic grasping, manipulation in clutter, and the integration of multi-modal sensory data. Liu’s major contribution lies in addressing the practical challenge of grasping order prediction—determining which object a robot should pick first when faced with a chaotic pile. His most cited paper, "Predicting Grasping Order in Clutter Environment by Using Both Color Image and Points Cloud" (2019, 9 citations), proposes a novel framework that fuses 2D color imagery with 3D point cloud data to sequentially plan grasps. This work moves beyond single-object grasping, a well-explored domain, to tackle the real-world complexity of overlapping and occluded objects. By explicitly modeling the influence objects have on one another in a cluttered scene, Liu’s research provides a critical stepping stone toward more autonomous and capable service robots. His contributions are particularly relevant for applications in domestic assistance and warehouse automation, where adaptability to messy, unpredictable settings is essential.
Research Focus
Key Achievements
Top Papers
- 1