In the field of robotic manipulation, the proficiency of deformable object manipulation lags behind human capabilities due to the inherent characteristics of deformable objects. These objects have infinite degrees of freedom, resulting in non-trivial perception and state estimation, and complex dynamics, complicating the prediction of future configurations. Although recent research has focused on deformable object manipulation, most approaches rely on static vision and simple manipulation techniques, limiting the performance level. This paper proposes two solutions to enhance the performance: interactive perception and the use of assistive tools. The first solution posits that optimal perspectives exist during deformable object manipulation, facilitating easier state estimation. By exploring the action-perception regularity, interactive perception facilitates better manipulation and perception. The second solution advocates for the use of assistive tools, a hallmark of human intelligence, to improve manipulation performance. For instance, a folding board can aid in garment folding tasks by reducing object deformation and managing complex dynamics. Hence, this research aims to address the deformable object manipulation problem by incorporating interactive perception and assistive tools to augment manipulation performance.

翻译：在机器人操作领域，可变形物体的操作水平仍落后于人类能力，这源于其固有特性：自由度数无穷大导致感知与状态估计复杂，动力学行为复杂使得未来构型预测困难。尽管近期研究聚焦于可变形物体操作，但多数方法仍依赖静态视觉和简单操作技术，限制了性能表现。本文提出两种提升性能的解决方案：交互式感知与辅助工具使用。第一种方案认为可变形物体操作过程中存在最优视角，可简化状态估计。通过探索动作-感知规律，交互式感知能够促进更佳的操作与感知。第二种方案主张使用辅助工具——人类智能的典型标志，用以提升操作性能。例如，折叠板可通过降低物体形变程度和控制复杂动力学，辅助完成衣物折叠任务。因此，本研究旨在通过融合交互式感知与辅助工具，提升可变形物体的操作性能。