Toshiki HIROGAKI
Papers
21
Total Citations
88
H-Index
5
About
Toshiki Hirogaki is a leading researcher in industrial robotics, with a focus on motion accuracy, calibration, and eco-friendly manufacturing. His work addresses critical challenges in offline teaching and variable production systems by developing deep learning and random forest methods to predict and compensate for positioning errors in large industrial robots—achieving over 12 and 11 citations, respectively. Hirogaki has also pioneered the use of dual-arm robots for precise motion control, including rolling ball dynamics on working plates and synchronous two-axis control, with several papers from 2012 garnering 5–9 citations. His contributions extend to sustainable manufacturing through fixed-abrasive polishing with compact robots, investigating material removal rates and pressing forces to reduce environmental impact. Notably, he has explored humanoid robots for industrial tasks using input shaping control and autonomous cooperation with passive balancers. With a career spanning over a decade, Hirogaki’s work is widely cited for its practical impact on robot accuracy, flexibility, and sustainability, making him a key figure in advancing intelligent and eco-conscious robotic systems for modern industry.
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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