深層予測モデル学習による可変剛性と素材変化を考慮した動的柔軟布操作

抄録

Dynamic manipulation of flexible objects such as cloth, which is difficult to modelize, is one of the major challenges in robotics. Humans can move their arms at high speed using their flexible bodies skillfully, and even when the material to be manipulated changes, they can manipulate the material after moving it several times and understanding its dynamics. Therefore, in this study, we focus on the following two points: (1) body control using a variable stiffness mechanism for dynamic manipulation, and (2) response to changes in the material of the manipulated object using parametric bias. By incorporating these two approaches into a deep prediction model, we show through experiments that a musculoskeletal humanoid can dynamically manipulate cloth while detecting changes in the physical properties of the manipulated object.