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：本文介绍了一个面向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，正在改变设计成果的共享与采纳方式。我们以一款线驱动、集成传感的软体手指为案例，对该工具箱进行了评估。对于此类兼具驱动与传感功能的器件，多目标优化能力自然成为刚需——因为至少需在驱动效果与传感性能这两个维度之间寻求平衡。因此，多目标优化是该工具箱的核心功能之一。通过对软体手指的优化实验，我们发现在实际制造的器件上，传感与驱动之间优化权衡的极端点确实在既定指标上相距甚远。此外，我们还深入分析了该案例的仿真-现实迁移行为，考虑了仿真网格密度、力学参数与制造公差等因素的影响。