Shinichi Kikuchi
Papers
2
Total Citations
153
H-Index
2
About
Shinichi Kikuchi is a robotics researcher whose work sits at the intersection of machine learning and robotic manipulation, with a particular focus on enabling intelligent physical interaction between robots and their environments. His most recognized contribution, "Learning Force Control for Contact-Rich Manipulation Tasks With Rigid Position-Controlled Robots" (2020), has garnered 150 citations and addresses one of the field's most persistent challenges: applying reinforcement learning to real-world robotic systems. While RL has demonstrated remarkable success in simulation, Kikuchi's research confronts the practical difficulties that arise when deploying these methods on physical hardware — particularly rigid, position-controlled manipulators, which present unique constraints for force-sensitive tasks. By developing approaches that bridge this sim-to-real gap, his work has made meaningful strides toward making autonomous robotic manipulation more accessible and deployable in real environments. His continued exploration of contact-rich manipulation, evidenced by related publications in the same domain, underscores a dedicated research agenda aimed at expanding the viability of learning-based control strategies beyond laboratory simulations and into practical robotic applications.
Research Focus
Key Achievements
Top Papers
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