In this paper, we introduce a novel open source toolbox for design optimization in Soft Robotics. We consider that design optimization is an important trend in Soft Robotics that is changing the way in which designs will be shared and adopted. We evaluate this toolbox on the example of a cable-driven, sensorized soft finger. For devices like these, that feature both actuation and sensing, the need for multi-objective optimization capabilities naturally arises, because at the very least, a trade-off between these two aspects has to be found. Thus, multi-objective optimization capability is one of the central features of the proposed toolbox. We evaluate the optimization of the soft finger and show that extreme points of the optimization trade-off between sensing and actuation are indeed far apart on actually fabricated devices for the established metrics. Furthermore, we provide an in depth analysis of the sim-to-real behavior of the example, taking into account factors such as the mesh density in the simulation, mechanical parameters and fabrication tolerances.

翻译：本文介绍了一款用于软体机器人设计优化的新型开源工具箱。我们认为设计优化是软体机器人领域的重要趋势，正在改变设计共享与采用的方式。我们以一款缆驱动、集成传感器的软体手指为例，对该工具箱进行了评估。对于这类兼具驱动与传感功能的装置，多目标优化需求自然产生——至少需要在两者之间寻求平衡。因此，多目标优化能力是该工具箱的核心特征之一。通过对软体手指的优化评估，我们发现：在已制造的实际设备上，传感与驱动之间的优化权衡极端点与既定指标确实存在显著差异。此外，我们深入分析了该案例的仿真到实际行为（sim-to-real），考虑了仿真网格密度、力学参数及制造公差等因素。