Ruihang Chu

Chinese University of Hong Kong, Beihang University

Papers

Total Citations

H-Index

About

Ruihang Chu is a robotics researcher whose work centers on robotic manipulation and human-robot interaction, with a particular focus on enabling robots to operate intelligently in unstructured, cluttered environments. His most significant contribution is the development of a novel approach for 6-DoF grasp pose estimation that simultaneously learns semantic and collision information. This work, published in 2021 and garnering 66 citations, directly addresses the long-standing challenge of robotic grasping in cluttered scenes. Unlike previous methods that rely on pre-known object geometry or multi-stage pipelines, Chu’s end-to-end learning framework allows a robot to understand both what an object is and how to safely approach it, making grasping more robust and efficient in real-world settings. Beyond manipulation, Chu has also advanced intuitive human-UAV interaction, creating a system where a hexacopter can be commanded through natural human poses, with onboard LEDs providing real-time feedback on the drone’s state and intent. This work, with 27 citations, demonstrates his commitment to making autonomous systems more accessible and responsive. Through his research, Chu is helping to bridge the gap between robotic capability and real-world complexity, pushing the boundaries of how robots perceive, interact with, and assist humans.