Yongjin Hou

Huazhong University of Science and Technology

Papers

Total Citations

H-Index

About

Yongjin Hou is a researcher in robotics and intelligent control, with a focus on adaptive manipulation and multi-robot coordination. His work centers on enabling robots to operate effectively in unstructured or unknown environments, addressing key challenges in compliance, autonomy, and distributed decision-making. In his highly cited 2020 paper, Hou introduced a variable impedance control framework for manipulators using Deep Q-Networks (DQN), a pioneering application of reinforcement learning to real-time physical interaction that allows robots to dynamically adjust their stiffness and damping in response to task demands. Building on this, his 2021 work developed a novel distributed control scheme for cooperative manipulation in unknown settings, where follower robots estimate the leader’s intended trajectory through network communication within a compliant control architecture. This approach enables seamless, decentralized coordination without requiring prior environmental models. Though early in his career, Hou’s contributions are already shaping the next generation of adaptive, collaborative robotic systems, laying the groundwork for safer and more flexible human-robot interaction in manufacturing, logistics, and field robotics.