Max Robotics — Global Service Robot Directory + US Certification

About

Haonan Duan is a leading researcher in the field of dexterous robotic manipulation, with a focus on enabling anthropomorphic hands to perform human-like grasping and object handovers. His work bridges the gap between human dexterity and robotic capability, addressing fundamental challenges in human-robot interaction. Duan’s most cited paper, “Robotics Dexterous Grasping: The Methods Based on Point Cloud and Deep Learning” (2021, 58 citations), provides a comprehensive survey of deep learning approaches for dexterous grasping, establishing a foundational framework for the field. He has made significant contributions to human-robot object handover, with multiple papers (25, 21, and 10 citations) developing reactive and learning-based methods for seamless handovers using anthropomorphic hands—a departure from traditional parallel-jaw grippers. His 2024 work on “Learning Human-Like Functional Grasping for Multifinger Hands From Few Demonstrations” (21 citations) tackles the challenge of generalizing functional grasps across diverse robotic hands with minimal training data. Duan’s recent comprehensive review (2025, 13 citations) synthesizes progress in human-like dexterous manipulation, highlighting advances in visual and tactile perception. His research is pivotal for advancing robots that can assist humans in daily life and industrial tasks, with a growing citation impact that underscores his influence in robotics.