Qianen Lai

State Key Laboratory of Industrial Control Technology, Zhejiang University

Papers

Total Citations

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About

Qianen Lai is a robotics researcher whose work centers on intelligent manipulation, specifically goal-oriented grasping and pre-grasp planning in cluttered environments. His major contribution lies in developing efficient learning frameworks that enable robots to synergize pushing and grasping actions—a critical capability for real-world scenarios where objects are densely packed or occluded. In his highly cited 2021 paper (84 citations), Lai introduced a method for learning push-grasping synergy that allows a robot to autonomously discover when a pre-grasp push is necessary to achieve a stable grasp on a target object, despite receiving positive rewards only upon successful grasping. This work addresses the sparse-reward challenge in reinforcement learning for manipulation. Additionally, his 2019 paper proposed a cascaded deep learning framework for real-time, robust grasp planning, balancing computational efficiency with reliability. With a total of over 90 citations across his key publications, Lai’s research is shaping the next generation of autonomous robotic systems capable of operating in unstructured environments—a foundational step toward practical service and industrial robots.