Papers
8
Total Citations
78
H-Index
5
About
Takao Nishi is a leading researcher in robotic manipulation and automation for logistics, with a focus on developing intelligent systems for warehouse and agricultural applications. His primary research areas include robot bin-picking, dual-arm manipulation, and object arrangement detection. Nishi’s most notable contribution is the development of a dual-arm manipulator system for random bin-picking, which integrates grasping and motion planning to enable robots to pick objects from piles, regrasp them between hands, and place them efficiently—a project that has garnered 30 citations. He further advanced the field with a motion planning algorithm for simultaneous two-object grasping, achieving 11 citations, and a shelf replenishment system that uses object arrangement detection and collapse prediction for bimanual manipulation (10 citations). Nishi also pioneered agricultural robotics with a mobile eggplant grading robot that uses machine vision for dynamic in-field variability sensing (9 citations). His recent work includes multi-step extraction planning from clutter and M3R-CNN, a multi-modal fusion method for instance segmentation in bin-picking. With over 78 citations across his key papers, Nishi’s research is pivotal in making robotic picking and packing more efficient, safe, and adaptable for real-world logistics and farming.
Research Focus
Key Achievements
Top Papers
- 1
- 2Efficient Picking by Considering Simultaneous Two-Object Grasping11 citations · 2021
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- 5Detection of object arrangement patterns using images for robot picking8 citations · 2018
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