Eiichi AOYAMA
Papers
19
Total Citations
77
H-Index
5
About
Eiichi Aoyama is a robotics researcher whose work spans industrial automation, humanoid manipulation, and precision manufacturing. His core contributions lie in improving the accuracy and dexterity of robotic systems—from large industrial arms to compact polishing robots. Notably, he pioneered the use of deep learning and random forest models to predict and calibrate positioning errors in large industrial robots, achieving citation counts of 12 and 11 respectively for these foundational studies. Aoyama has also advanced dual-arm robot control, developing methods to synchronize two-axis plate motion and enable rolling-ball manipulation for high-precision tasks. His research extends to humanoid robotics, where he has explored impact control using input shaping and autonomous cooperation with passive balancers. In a creative departure, Aoyama even demonstrated a musical saw-playing humanoid robot with passive sound feedback, showcasing the breadth of his innovation. With over 60 citations across his most-cited works, Aoyama’s research is driving the next generation of flexible, accurate, and collaborative robotic systems for both industrial and human-occupied environments.
Research Focus
Key Achievements
Top Papers
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- 2Positioning Error Calibration of Industrial Robots Based on Random Forest11 citations · 2021
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