A generalizable equilibrium model for bending soft arms with longitudinal actuators
A generalizable equilibrium model for bending soft arms with longitudinal actuators
复制标题
DOI：
10.1177/0278364919880259
复制
发表时间：
2019-10
期刊：
影响因子：
--
通讯作者：
G. Olson;Scott Chow;A. Nicolai;C. Branyan;Geoffrey A. Hollinger;Y. Mengüç
中科院分区：
文献类型：
--
作者：
G. Olson;Scott Chow;A. Nicolai;C. Branyan;Geoffrey A. Hollinger;Y. Mengüç
目前的软臂弯曲模型是根据实验确定的臂特定参数制定的，无法评估软机器人臂设计的根本差异。现有模型成功地改善了对单个手臂的控制，但没有深入了解手臂的结构如何影响手臂的能力。例如，全向软机器人手臂最常见地具有三个并行致动器，但也可能具有四个或更多，而包括章鱼在内的常见生物手臂具有数十个不同的纵向肌束。本文基于平衡原理并假设中性轴位置未知，提出了用纵向致动器弯曲的软臂的准静态分析模型。该模型作为一个通用框架呈现，专门用于具有 N 个流体驱动致动器的手臂，其中一个子集被加压以引起具有一定曲率和方向的弯曲。使用平面（2D）和空间（3D）弯曲对所提出的实现进行了实验验证。平面模型用于初始估计闭环曲率控制系统的压力，并限制快速探索随机树 (RRT) 运动规划器的可访问配置。演示了三段平面臂沿着计划的轨迹穿过墙壁的间隙。最后，该模型用于探索手臂形态如何影响最大曲率和方向分辨率。这项研究分析地将软臂结构和执行器行为与空载臂性能联系起来，其结果可用于系统地设计软机器人臂。
Current models of bending in soft arms are formulated in terms of experimentally determined, arm-specific parameters, which cannot evaluate fundamental differences in soft robot arm design. Existing models are successful at improving control of individual arms but do not give insight into how the structure of the arm affects the arm’s capabilities. For example, omnidirectional soft robot arms most frequently have three parallel actuators, but may have four or more, while common biological arms, including octopuses, have tens of distinct longitudinal muscle bundles. This article presents a quasi-static analytical model of soft arms bent with longitudinal actuators, based on equilibrium principles and assuming an unknown neutral axis location. The model is presented as a generalizable framework and specifically implemented for an arm with N fluid-driven actuators, a subset of which are pressurized to induce a bend with a certain curvature and direction. The presented implementation is validated experimentally using planar (2D) and spatial (3D) bends. The planar model is used to initially estimate pressure for a closed-loop curvature control system and to bound the accessible configurations for a rapidly-exploring random trees (RRT) motion planner. A three-segment planar arm is demonstrated to navigate along a planned trajectory through a gap in a wall. Finally, the model is used to explore how the arm morphology affects maximum curvature and directional resolution. This research analytically connects soft arm structure and actuator behavior to unloaded arm performance, and the results may be used to methodically design soft robot arms.