Department of Aerospace, California Institute of Technology, Pasadena, California.
NASA Ames Research Center, Moffett Field, California.
Soft Robot. 2020 Jun;7(3):346-361. doi: 10.1089/soro.2019.0056. Epub 2020 Feb 7.
Soft spherical tensegrity robots are novel steerable mobile robotic platforms that are compliant, lightweight, and robust. The geometry of these robots is suitable for rolling locomotion, and they achieve this motion by properly deforming their structures using carefully chosen actuation strategies. The objective of this work is to consolidate and add to our research to date on methods for realizing rolling locomotion of spherical tensegrity robots. To predict the deformation of tensegrity structures when their member forces are varied, we introduce a modified version of the dynamic relaxation technique and apply it to our tensegrity robots. In addition, we present two techniques to find desirable deformations and actuation strategies that would result in robust rolling locomotion of the robots. The first one relies on the greedy search that can quickly find solutions, and the second one uses a multigeneration Monte Carlo method that can find suboptimal solutions with a higher quality. The methods are illustrated and validated both in simulation and with our hardware robots, which show that our methods are viable means of realizing robust and steerable rolling locomotion of spherical tensegrity robots.
软球形张拉整体机器人是一种新型的可操纵移动机器人平台,具有柔顺性、重量轻和鲁棒性等特点。这些机器人的几何形状适合滚动运动,它们通过使用精心选择的致动策略适当改变结构的形状来实现这种运动。本工作的目的是整合和扩展我们迄今为止在实现球形张拉整体机器人滚动运动的方法上的研究。为了预测张拉整体结构在改变其构件力时的变形,我们引入了一种改进的动力松弛技术,并将其应用于我们的张拉整体机器人中。此外,我们还提出了两种技术来寻找理想的变形和致动策略,从而实现机器人的稳健滚动运动。第一种技术依赖于可以快速找到解决方案的贪婪搜索,第二种技术则使用多代蒙特卡罗方法,可以找到具有更高质量的次优解。这些方法在模拟和我们的硬件机器人中进行了说明和验证,结果表明,我们的方法是实现球形张拉整体机器人稳健和可操纵滚动运动的可行手段。