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：摘要：软体机器人具有独特能力，但受限于缺乏可扩展的构建技术，以及依赖于软体动力学、高维驱动模式及外部/机载力的高效控制与运动算法的复杂性。本文提出可扩展的方法与平台，用于研究质量分布和驱动模式对完全无束缚模块化软体机器人的影响。我们开发了可扩展振动智能压电机器人（eViper）平台，并基于PyBullet构建了开源的类电活性机器人薄片仿真框架（SFERS），以研究复杂的质量-运动交互机制。通过集成机载电力电子器件、传感器、驱动器和电池，eViper平台支持快速迭代设计与评估不同质量分布和驱动阵列控制策略，并借助自动数据采集能力同时支撑基于物理的建模与数据驱动建模。研究表明，SFERS可为优化eViper的质量分布与驱动模式提供有效指导，从而实现最大速度或最低运输成本（COT）。