Momomi Kanamura

Papers

Total Citations

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About

Momomi Kanamura is a robotics researcher whose work sits at the intersection of deep learning and dexterous manipulation. Her primary research areas include robotic rope handling, dual-arm coordination, and educational robotics for artificial intelligence. Kanamura’s most significant contribution is the successful execution of in-air knotting of rope using a dual-arm two-finger robot guided by deep learning—a task that demands real-time adaptation to a constantly changing, flexible material. This work, her most cited with 26 citations, demonstrates a breakthrough in handling deformable objects, a notoriously difficult challenge in robotics. She also developed a basic educational kit that systematically integrates robotic systems with deep neural networks, addressing a critical gap in accessible learning tools for beginners. With a total of 37 citations across her top papers, Kanamura’s research is gaining traction for its practical, hands-on approach to complex robotic control. Her achievements highlight a commitment to both advancing the frontier of autonomous manipulation and lowering the barrier to entry for students and researchers entering the field of deep learning–driven robotics.