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The aim is to summarize advancements and challenges in deep learning approaches for cloth manipulation tasks.

Deep learning-based robotic cloth manipulation applications: systematic review, challenges and opportunities for physical AI

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The aim is to summarize advancements and challenges in deep learning approaches for cloth manipulation tasks.
Systematic review of 41 relevant papers from 2019 to 2024
Analysis of factors influencing cloth unfolding and folding
Evaluation of current algorithms and their effectiveness
Identification of challenges like irregular cloth sizes and initial states
Discussion of future perspectives and necessary improvements.
Current methods demonstrate strong performance but face significant challenges
Need for improved real-world data and realistic cloth simulators
Incorporation of multi-modal sensors can enhance performance
Emphasizes the need for consistent comparison metrics
Highlights open problems in learning and control paradigms.

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This review examines deep learning applications in cloth manipulation, highlighting challenges and future opportunities.

Gu et al. (2026) studied this question.

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