Kiyoto Ito
Papers
6
Total Citations
59
H-Index
3
About
Kiyoto Ito is a leading researcher in robotic manipulation and automation for logistics, with a focus on developing intelligent systems that can handle the complex, unstructured environments of modern warehouses. His work centers on three key areas: mobile dual-arm robotics for automated order picking, advanced tactile sensing and grasp control, and 3D object pose estimation for mixed-item handling. Ito’s most impactful contribution is the design and prototyping of a mobile dual-arm robot that autonomously navigates, recognizes diverse products, and executes precise picking operations—a system that has garnered 25 citations and set a benchmark for warehouse automation. He also pioneered an action-intention-based grasp control method using a combined optical-mechanical tactile sensor (24 citations), enabling non-professional users to easily manipulate objects of varying weight and hardness. More recently, Ito has advanced category-level 3D object matching with his PABSCO method, which reduces preparation costs while maintaining high recognition accuracy for multi-part items. His scalable robotic-hand control architecture further demonstrates his commitment to practical, sensor-rich systems. With a career spanning foundational tactile sensing to cutting-edge pose estimation, Ito’s work directly addresses the real-world challenges of logistics automation, making him a key figure in the field.
Research Focus
Key Achievements
Top Papers
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