Domain Randomization for Robust, Affordable and Effective Closed-Loop Control of Soft Robots

Tiboni, Gabriele; Protopapa, Andrea; Tommasi, Tatiana; Averta, Giuseppe

doi:10.1109/iros55552.2023.10342537

2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2023

DOI: 10.1109/iros55552.2023.10342537

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Domain Randomization for Robust, Affordable and Effective Closed-Loop Control of Soft Robots

Gabriele Tiboni,

Andrea Protopapa,

Tatiana Tommasi

et al.

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2024

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Learning Controllers for Continuum Soft Manipulators: Impact of Modeling and Looming Challenges

Falotico,

Donato,

Alessi

et al. 2024

Advanced Intelligent Systems

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Soft manipulators, renowned for their compliance and adaptability, hold great promise in their ability to engage safely and effectively with intricate environments and delicate objects. Nonetheless, controlling these soft systems presents distinctive hurdles owing to their nonlinear behavior and complicated dynamics. Learning‐based controllers for continuum soft manipulators offer a viable alternative to model‐based approaches that may struggle to account for uncertainties and variability in soft materials, limiting their effectiveness in real‐world scenarios. Learning‐based controllers can be trained through experience, exploiting various forward models that differ in physical assumptions, accuracy, and computational cost. In this article, the key features of popular forward models, including geometrical, pseudo‐rigid, continuum mechanical, or learned, are first summarized. Then, a unique characterization of learning‐based policies, emphasizing the impact of forward models on the control problem and how the state of the art evolves, is offered. This leads to the presented perspectives outlining current challenges and future research trends for machine‐learning applications within soft robotics.

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Learning Controllers for Continuum Soft Manipulators: Impact of Modeling and Looming Challenges

Falotico,

Donato,

Alessi

et al. 2024

Advanced Intelligent Systems

View full text Add to dashboard Cite

show abstract

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Domain Randomization for Robust, Affordable and Effective Closed-Loop Control of Soft Robots

Cited by 1 publication

References 33 publications

Learning Controllers for Continuum Soft Manipulators: Impact of Modeling and Looming Challenges

Learning Controllers for Continuum Soft Manipulators: Impact of Modeling and Looming Challenges

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