Machines that mimic humans have inspired scientists for centuries. Bio-inspired soft robotic hands are a good example of such an endeavor, featuring intrinsic material compliance and continuous motion to deal with uncertainty and adapt to unstructured environments. Recent research led to impactful achievements in functional designs, modeling, fabrication, and control of soft robots. Nevertheless, the full realization of life-like movements is still challenging to achieve, often based on trial-and-error considerations from design to fabrication, consuming time and resources. In this study, a soft robotic hand is proposed, composed of soft actuator cores and an exoskeleton, featuring a multi-material design aided by finite element analysis (FEA) to define the hand geometry and promote finger's bendability. The actuators are fabricated using molding and the exoskeleton is 3D-printed in a single step. An ON-OFF controller keeps the set fingers' inner pressures related to specific bending angles, even in the presence of leaks. The FEA numerical results were validated by experimental tests, as well as the ability of the hand to grasp objects with different shapes, weights and sizes. This integrated solution will make soft robotic hands more available to people, at a reduced cost, avoiding the time-consuming design-fabrication trial-and-error processes.

翻译：模仿人类的机器几个世纪以来一直启发着科学家。仿生软体机械手正是此类探索的典范，其凭借内在的材料柔顺性与连续运动能力，可应对不确定性并适应非结构化环境。近年来，研究在软体机器人的功能性设计、建模、制造与控制领域取得了突破性进展。然而，完全实现类生命体运动仍面临挑战，当前设计到制造流程往往依赖反复试错，耗时且耗费资源。本研究提出一种由软体执行器核心与外骨骼构成的软体机械手，采用基于有限元分析（FEA）的多材料设计方法，以定义手部几何形状并提升手指弯曲性能。执行器通过模塑工艺制造，外骨骼则采用3D打印一步成型。通过ON-OFF控制器，即使在存在泄漏的情况下，也能保持设定手指内压与特定弯曲角度的对应关系。实验测试验证了有限元分析数值结果的准确性，并证实了该机械手抓取不同形状、重量及尺寸物体的能力。这种集成方案将以更低的成本提升软体机械手的普及性，同时避免耗时的设计-制造试错流程。