Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, 420 Westwood Plaza, Los Angeles, CA, 90095, USA.
Department of Mechanical Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, 15213, USA.
Nat Commun. 2020 May 6;11(1):2233. doi: 10.1038/s41467-020-15651-9.
Soft robots are primarily composed of soft materials that can allow for mechanically robust maneuvers that are not typically possible with conventional rigid robotic systems. However, owing to the current limitations in simulation, design and control of soft robots often involve a painstaking trial. With the ultimate goal of a computational framework for soft robotic engineering, here we introduce a numerical simulation tool for limbed soft robots that draws inspiration from discrete differential geometry based simulation of slender structures. The simulation incorporates an implicit treatment of the elasticity of the limbs, inelastic collision between a soft body and rigid surface, and unilateral contact and Coulombic friction with an uneven surface. The computational efficiency of the numerical method enables it to run faster than real-time on a desktop processor. Our experiments and simulations show quantitative agreement and indicate the potential role of predictive simulations for soft robot design.
软体机器人主要由软体材料组成，这使得它们能够进行机械上强大的动作，而这在传统的刚性机器人系统中通常是不可能的。然而，由于目前在软体机器人的模拟、设计和控制方面存在的限制，往往需要进行艰苦的试验。为了实现软体机器人工程的计算框架，我们在这里引入了一种基于离散微分几何的数值模拟工具，用于模拟有腿的软体机器人。该模拟方法受到基于离散微分几何的细长结构模拟的启发，模拟中对肢体的弹性、软体与刚性表面之间的非弹性碰撞，以及与不平坦表面的单侧接触和库仑摩擦进行了隐式处理。数值方法的计算效率使其能够在桌面处理器上实时运行。我们的实验和模拟结果表明，数值方法具有定量一致性，并表明预测性模拟在软体机器人设计中的潜在作用。
