A Q-learning Control Method for a Soft Robotic Arm Utilizing Training Data from a Rough Simulator

Li, Peijin; Wang, Gaotian; Jiang, Hao; Jin, Yusong; Gan, Yinghao; Chen, Xiaoping; Ji, Jianmin

doi:10.1109/robio54168.2021.9739524

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Cited by 4 publications

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Trimmed helicoids: an architectured soft structure yielding soft robots with high precision, large workspace, and compliant interactions

Guan,

Stella,

Della Santina

et al. 2023

npj Robot

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The development and use of architectured structures is changing the means by which we design and fabricate soft robots. These materials utilize their topology and geometry to control physical and mechanical structural properties. We propose an architectured structure based on trimmed helicoids that allows for independent regulation of the bending and axial stiffness which facilitates tuneability of the resulting soft robot properties. Leveraging FEA and computational analysis we select a geometry that provides an optimal trade-off between controllability, sensitivity to errors in control, and compliance. By combining these modular trimmed helicoid structures in conjunction with control methods, we demonstrate a meter-scale soft manipulator that shows control precision, large workspace, and compliant interactions with the environment. These properties enable the robot to perform complex tasks that leverage robot-human and robot-environment interactions such as human feeding and collaborative object manipulation.

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