Soft robots present unique capabilities, but have been limited by the lack of scalable technologies for construction and the complexity of algorithms for efficient control and motion, which depend on soft-body dynamics, high-dimensional actuation patterns, and external/on-board forces. This paper presents scalable methods and platforms to study the impact of weight distribution and actuation patterns on fully untethered modular soft robots. An extendable Vibrating Intelligent Piezo-Electric Robot (eViper), together with an open-source Simulation Framework for Electroactive Robotic Sheet (SFERS) implemented in PyBullet, was developed as a platform to study the sophisticated weight-locomotion interaction. By integrating the power electronics, sensors, actuators, and batteries on-board, the eViper platform enables rapid design iteration and evaluation of different weight distribution and control strategies for the actuator arrays, supporting both physics-based modeling and data-driven modeling via on-board automatic data-acquisition capabilities. We show that SFERS can provide useful guidelines for optimizing the weight distribution and actuation patterns of the eViper to achieve the maximum speed or minimum cost-of-transportation (COT).

翻译：软体机器人展现出独特的能力，但受限于缺乏可扩展的构造技术以及高效控制与运动算法的复杂性——这些算法依赖于软体动力学、高维驱动模式以及外部/机载力。本文提出了可扩展的方法与平台，用于研究重量分布与驱动模式对完全无缆模块化软体机器人的影响。我们开发了可扩展的振动智能压电机器人（eViper）及其开源的基于PyBullet实现的电活性机器人薄片仿真框架（SFERS），作为研究复杂重量-运动相互作用关系的平台。通过将电力电子器件、传感器、执行器与电池集成于机载系统，eViper平台支持针对执行器阵列的不同重量分布与控制策略进行快速设计迭代与评估，并借助机载自动数据采集能力同时支撑基于物理的建模与数据驱动的建模。研究结果表明，SFERS可为优化eViper的重量分布与驱动模式提供有效指导，以实现最大速度或最小运输成本（COT）。