Shun Hasegawa
Papers
17
Total Citations
177
H-Index
7
About
Shun Hasegawa is a roboticist specializing in dexterous manipulation, grasping in cluttered environments, and multi-modal robotic hands. His major contributions center on developing novel gripper designs and control strategies that combine suction and multi-fingered grasping to handle diverse objects in confined spaces—critical for warehouse automation. His most cited work, “A three-fingered hand with a suction gripping system for picking various objects in cluttered narrow space” (51 citations), introduces the Suction Pinching Hand, which merges vacuum suction with finger pinching to overcome the limitations of traditional grippers in obstacle-dense settings. Hasegawa also advanced proximity sensing for robust object search and grasp, as seen in his 2018 paper (22 citations), and pioneered GraspFusion (22 citations), a deep learning framework that fuses multiple grasp modalities with instance segmentation. His research on online sensor model acquisition (10 citations) and detecting folded objects (10 citations) further demonstrates his impact on real-world robotic picking. With over 150 total citations, Hasegawa’s work bridges hardware innovation and intelligent control, pushing the boundaries of autonomous manipulation in logistics and service robotics.
Research Focus
Key Achievements
Top Papers
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- 2A Gripper for Object Search and Grasp Through Proximity Sensing22 citations · 2018
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