Direct Encoding of Tunable Stiffness Into an Origami-Inspired Jumping Robot Leg
Direct Encoding of Tunable Stiffness Into an Origami-Inspired Jumping Robot Leg
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DOI：
10.1115/1.4056958
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发表时间：
2024-03-01
影响因子：
2.6
通讯作者：
Aukes, Daniel M.
中科院分区：
文献类型：
--
作者：
Chen, Fuchen;Aukes, Daniel M.
机器人腿的刚度对腿的运动性能影响很大；然而，调整这种刚度可能是一项昂贵而复杂的任务。本文采用折纸启发的层压板设计制造方法，对跳跃机器人腿的刚度进行了直接调整。除了胡克定律所描述的刚度系数外，力-位移曲线的非线性也可以通过优化机构的几何结构来调节。该方法减少了实现不同刚度腿所需的零件数量，简化了人工重新设计的工作量，降低了腿式机器人的成本，加快了设计和优化过程。我们制作并测试了六种不同的刚度曲线，这些曲线的非线性和系数都不同。通过直流电机驱动的垂直跳跃实验，我们还表明，适当调整腿刚度可以使起跳速度提高18%，峰值输出功率提高19%。
The stiffness of robot legs greatly affects legged locomotion performance; tuning that stiffness, however, can be a costly and complex task. In this paper, we directly tune the stiffness of jumping robot legs using an origami-inspired laminate design and fabrication method. In addition to the stiffness coefficient described by Hooke's law, the nonlinearity of the force-displacement curve can also be tuned by optimizing the geometry of the mechanism. Our method reduces the number of parts needed to realize legs with different stiffness while simplifying manual redesign effort, lowering the cost of legged robots while speeding up the design and optimization process. We have fabricated and tested the leg across six different stiffness profiles that vary both the nonlinearity and coefficient. Through a vertical jumping experiment actuated by a DC motor, we also show that proper tuning of the leg stiffness can result in an 18% improvement in lift-off speed and an increase of 19% in peak power output.