Papers

8

Total Citations

115

H-Index

5

About

Shuichi Akizuki is a leading researcher in robotic manipulation, whose work bridges the gap between human-like intelligence and practical automation. His primary research areas include affordance-based grasping, bin-picking, and human-robot interaction for education. Akizuki’s most influential contribution is his seminal review on affordance in robotic manipulation (2017, 65 citations), which established a framework for applying Gibson’s ecological psychology to enable robots to perceive action possibilities in objects—a key step toward advanced, human-like manipulation. He has also made significant strides in industrial robotics, developing a stable 3D pose estimation method for randomly stacked parts (2015, 9 citations) and a multi-gripper switching strategy for diverse bin-picking (2019, 13 citations). Notably, his team achieved recognition at the Amazon Picking Challenge 2016 and the World Robot Summit 2020, demonstrating robust, jigless assembly. More recently, Akizuki has ventured into educational robotics, proposing a learning support model that adapts to learners’ perplexed facial expressions (2024, 8 citations). With over 100 total citations, his work continues to shape both industrial automation and socially interactive robots.

Research Focus

Key Achievements

5
H-Index
8
Papers
115
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
A brief review of affordance in robotic manipulation research
65 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 33
🏛 Institutions: Keio University, Chukyo University, Suzuka University of Medical Science

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago