Bruder Daniel, Graule Moritz A, Teeple Clark B, Wood Robert J
John A. Paulson School of Engineering and Applied Sciences, Harvard University, 150 Western Ave., Boston, MA 02134, USA.
Sci Robot. 2023 Aug 30;8(81):eadf9001. doi: 10.1126/scirobotics.adf9001.
Soft robot arms offer safety and adaptability due to their passive compliance, but this compliance typically limits their payload capacity and prevents them from performing many tasks. This paper presents a model-based design approach to effectively increase the payload capacity of soft robot arms. The proposed approach uses localized body stiffening to decrease the compliance at the end effector without sacrificing the robot's range of motion. This approach is validated on both a simulated and a real soft robot arm, where experiments show that increasing the stiffness of localized regions of their bodies reduces the compliance at the end effector and increases the height to which the arm can lift a payload. By increasing the payload capacity of soft robot arms, this approach has the potential to improve their efficacy in a variety of tasks including object manipulation and exploration of cluttered environments.
柔性机器人手臂因其被动柔顺性而具有安全性和适应性，但这种柔顺性通常会限制其 payload 能力，并使其无法执行许多任务。本文提出了一种基于模型的设计方法，以有效提高柔性机器人手臂的 payload 能力。所提出的方法使用局部身体硬化来降低末端执行器的柔顺性，而不牺牲机器人的运动范围。该方法在模拟和真实的柔性机器人手臂上均得到验证，实验表明，增加其身体局部区域的刚度可降低末端执行器的柔顺性，并增加手臂能够举起 payload 的高度。通过提高柔性机器人手臂的 payload 能力，该方法有可能提高其在包括物体操纵和杂乱环境探索等各种任务中的效能。
