Xiaoming Duan

Papers

Total Citations

H-Index

About

Xiaoming Duan is an emerging researcher in the field of robotic manipulation and autonomous systems, with a particular focus on intelligent perception and motion planning for robotic grasping. His work addresses one of the most challenging problems in modern robotics: enabling robots to reliably grasp objects in cluttered, real-world environments where targets may be partially hidden or occluded. His most notable contribution, the AffordanCE-driven Next-Best-View planning policy (ACE-NBV), published in 2023, represents a significant step forward in active perception for robotics. By leveraging affordance information to guide viewpoint selection, his approach allows robotic systems to intelligently explore scenes and identify feasible grasping opportunities — a capability critical for complex manipulation tasks in unstructured settings. The paper has already garnered 6 citations since its publication, reflecting growing interest from the robotics research community. Duan's research sits at the intersection of computer vision, machine learning, and robotics, contributing practical solutions to longstanding challenges in grasp planning and scene understanding. His work holds strong promise for real-world applications in areas such as warehouse automation, assistive robotics, and industrial manipulation systems.