Ichiro Sakuma — accepted AI-conference papers

2024

SurgEM: A Vision-Based Surgery Environment Modeling Framework for Constructing a Digital Twin Toward Autonomous Soft Tissue Manipulation

Jiahe Chen, Etsuko Kobayashi, Ichiro Sakuma, Naoki Tomii

RA-L 2024

Autonomous soft tissue manipulation in robotic surgery remains challenging. Modeling the tool-tissue interaction, analyzing the tissue structural deformation and monitoring the biomechanical status during surgery manipulation may benefit the development of autonomous surgery; however, there are curr

Cited by 7 Source ↗Scholar ↗

2023

Learning Robotic Insertion Tasks From Human Demonstration

Kaimeng Wang, Yu Zhao, Ichiro Sakuma

RA-L 2023

Robotic insertion tasks often rely on delicate manual tuning due to the complexity of contact dynamics. In contrast, human is remarkably efficient in these tasks. In this context, Programming by Demonstration (PbD) has gained much traction since it shows the possibility for robots to learn new skill

Cited by 14 Source ↗Scholar ↗