Masahiro Kamigaki
Papers
2
Total Citations
8
H-Index
2
About
Masahiro Kamigaki is a researcher advancing the frontier of robot-environment interaction, with a focus on soft contact motion and impedance control. His work addresses a critical challenge in industrial automation: enabling robots to safely and effectively interact with their surroundings. In his highly cited 2022 paper, "Fast soft contact motion using force control with virtual viscosity field," Kamigaki introduced a novel method for achieving rapid yet gentle physical contact, a key capability for tasks requiring precision and safety. His 2020 study, "Learning Impedance Distribution of Object from Images Using Fully Convolutional Neural Networks," pioneered the use of deep learning to infer the mechanical impedance of objects directly from visual data—a significant step toward robots that can adapt their contact behavior without prior knowledge. Though early in his career, Kamigaki’s work has already garnered attention, with each of these papers accumulating 4 citations. By bridging force control, computer vision, and neural networks, he is laying the groundwork for more intelligent and autonomous robotic systems capable of operating in unstructured environments.
Research Focus
Key Achievements
Top Papers
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