Ningquan Gu

Wuhan Textile University, Tohoku University

Papers

Total Citations

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About

Ningquan Gu is a rising star in robotic manipulation, specializing in deformable object handling and bimanual control. His research focuses on enabling robots to perform complex tasks with garments, bags, and other non-rigid materials, bridging the gap between dynamic and quasi-static manipulation strategies. Gu’s most-cited work, “Learning to Unfold Garment Effectively Into Oriented Direction” (2023, 13 citations), introduces a policy that strategically selects between dynamic fling and pick-and-place actions to orient garments for downstream folding—a critical step toward practical robotic laundry assistance. In “ShakingBot: dynamic manipulation for bagging” (2024, 8 citations), he tackles the notoriously difficult problem of bag manipulation, using dynamic shaking to open and handle plastic bags, demonstrating robust perception and control for real-world logistics. His latest contribution, “TactileAloha: Learning Bimanual Manipulation With Tactile Sensing” (2025, 6 citations), integrates tactile sensors into the Aloha bimanual platform, enabling fine-grained texture perception for tasks where vision alone fails. Though early in his career, Gu’s work has already garnered attention for its practical focus on everyday deformable objects, and his integration of tactile sensing marks a notable step toward more dexterous, human-like robotic manipulation.