Sakura YAMAGUCHI

Real-to-real 2D crawling gait learning for a tendon-driven soft caterpillar robot

Ryuma Niiyama, Sakura YAMAGUCHI, Koichi TEZUKA

Soft robots exhibit rich deformation and contact interactions that are particularly suited to crawling locomotion. At the same time, these properties make modeling and control challenging, especially in systems with continuous deformation and strong ground contact. While simulation-based reinforcement learning has been …

jp (code pays fourni par la source)

Wire-Driven Reconfigurable Soft Modular Robot for Multi-Modal Locomotion

Sakura YAMAGUCHI, Ryuma Niiyama

Soft locomotion robots, leveraging compliant materials, adapt well to complex terrains, yet research evaluating variations in body configuration and achieving multiple locomotion modes within a single system remains limited. We present a reconfigurable soft modular robot combining urethane chip foam flexibility with …

jp (code pays fourni par la source)

Reinforcement Learning-Based 2D Planar Locomotion Generation for Tendon-Driven Soft Robot

Sakura YAMAGUCHI, Koichi TEZUKA, Ryuma Niiyama

jp (code pays fourni par la source)

Multi-DoF tendon-driven inflatable robotic arm

Sakura YAMAGUCHI, Masayuki Otsuka, Kiyohumi FUJINO, Ryuma Niiyama

An inflatable structure has the following characteristics: flexible, safe, lightweight, and low-cost. Because of these, it is expected to be applied to robots that make safe contact with humans. Conventional inflatable robotic arms (IRAs) are divided into multiple chambers for each joint, …

jp (code pays fourni par la source)