Impact Invariant Control with Applications to Bipedal Locomotion

Impact Invariant Control with Applications to Bipedal Locomotion
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冲击不变控制及其在双足运动中的应用

DOI:
10.1109/iros51168.2021.9636094
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发表时间:
2021
期刊:
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
影响因子:
--
通讯作者:
Michael Posa
Michael Posa
中科院分区:
--
文献类型:
--
作者:
William Yang;Michael Posa

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当有腿的机器人影响它们的环境时,它们会在很短的时间内经历速度的巨大变化。测量和应用对这些速度的反馈是具有挑战性的,并且由于撞击模型和撞击时机的不确定性而更加复杂。这项工作提出了一个通用的框架,通过将控制目标投影到一个与碰撞事件不变的子空间来适应碰撞过程中的反馈控制。所得到的控制器对碰撞事件中的不确定性具有鲁棒性,同时保持对碰撞不变子空间的最大控制权威。我们演示了投影在平面五连杆两足动物行走控制器和柔顺三维两足机器人Cassie跳跃控制器上的应用。实验结果表明,该方法在硬件上具有很好的可移植性。
When legged robots impact their environment, they undergo large changes in their velocities in a small amount of time. Measuring and applying feedback to these velocities is challenging, and is further complicated due to uncertainty in the impact model and impact timing. This work proposes a general framework for adapting feedback control during impact by projecting the control objectives to a subspace that is invariant to the impact event. The resultant controller is robust to uncertainties in the impact event while maintaining maximum control authority over the impact invariant subspace. We demonstrate the utility of the projection on a walking controller for a planar five-link-biped and on a jumping controller for a compliant 3D bipedal robot, Cassie. The effectiveness of our method is shown to translate well on hardware.
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