A Tensegrity Joint for Low-Inertia, Compact, and Compliant Soft Manipulators

ADVANCED INTELLIGENT SYSTEMS(2024)

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摘要
Compact, low-inertia, and soft compliant robotic joint mechanisms are in great demand for ensuring safe interactions in human-robot collaborative tasks. Tensegrity, of which the structural integrity is constrained by tension, does not involve static/sliding friction among the rigid components. However, this mechanical stability is very susceptible to actuation errors. It requires complex kinematics modeling and sophisticated control model with sensing feedback. Herein, a low-inertia tensegrity joint that is covered/protected by a fiber Bragg grating (FBG)-embedded silicone sheath is proposed, with the aim to reinforce the joint motion stability and enable self-contained sensing feedback. A learning-based closed-loop controller is also designed and trained with the proper joint configurations selected by a two-step sampling method. Both the kinematics and static equilibriums of such configurations can be well satisfied. The experiments demonstrate that the joint can follow paths accurately in 2D by compensating manipulation error shortly under the closed-loop control. The joint stiffness can also be varied against the external/impulsive disturbances. It can be foreseen that this primitive robot joint component with 2 degrees of freedom (DoFs) can provide safe, compliant interaction with human, for which a simple test of maneuvering a portable ultrasound probe (& AP;210 g) for abdominal imaging is demonstrated.
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关键词
fiber Bragg grating (FBG),learning-based control,soft manipulator,tensegrity,variable stiffness
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