提出可预测大尺寸软机械臂抗重力性能的几何优化方法
Design Optimization for Large High-Force Soft Robot Manipulators Under Gravitational Loads
- 基于抗屈曲约束，优化软机械臂几何结构以最大化阻塞力
- 实验验证三种构型中该方法能准确预测最大末端输出力
- 闭式解支持设计前评估，适合大型人机交互软机器人研发
设计能够产生高作用力的大尺寸软体机器人进行人机物理交互仍面临重大挑战。以往研究多聚焦于概念原型，缺乏系统性框架来判断设计范式是否适配特定任务。本文提出一种软机械臂几何优化方法，在自重载荷下满足抗屈曲约束的同时最大化其阻塞力。在特定假设下，该优化问题存在显式解。通过三种大尺寸、气动驱动软机械臂构型的实验，验证了该方法能准确预测哪些设计满足约束条件，并产生最大末端执行器力。该方法具有闭式解，可使设计者在前期判断某类软机械臂在大尺度物理交互中的适用性。
原文摘要 · Abstract (English)
Designing large soft robots capable of generating high forces for physical human-robot interaction remains a significant challenge in soft robotics. Prior work in large soft robots has focused on proof-of-concept prototypes, and no systematic framework exists for determining the suitability of a design paradigm for a desired task. This manuscript introduces a method for optimizing the geometry of a soft robot limb, maximizing its blocking force subject to an anti-bucking constraint under its own gravitational loading. We demonstrate that an explicit solution exists to the proposed optimization problem under certain assumptions. Experiments with three geometries of a large, soft, pneumatically-actuated manipulator demonstrate that the method correctly predicts which designs meet constraints and which produces the largest end-effector forces. This method, with its closed-form solution, can allow designers to determine a-priori if an intended class of soft manipulators is an appropriate choice for physical interaction at large size scales.
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