Page 21 - Read Online
P. 21

Page 18 of 26                                                         Chen et al. Soft Sci. 2026, 6, 3





               Despite significant progress, critical barriers remain for clinical translation, such as long-term materials
               biostability and safety, real-time closed-loop control methods, and scalable reproducible manufacturing
               procedures. Overcoming these challenges requires interdisciplinary innovation across materials science,
               robotics, bioengineering, and regulatory science.


               DECLARATIONS
               Authors’ contributions
               Designed and organized the project: Chen, Z.; Yang, S.; Law, J.; Du, X.; Sun, Y.
               Manuscript writing: Chen, Z.; Yang, S.
               Manuscript supervision: Law, J.; Du, X.; Sun, Y.
               All authors have given approval to the final version of the manuscript.

               Availability of data and materials
               Not applicable.

               Financial support and sponsorship
               This research is financially supported by the National Natural Science Foundation of China (Grant Nos.
               52505004 and 62588301) and the Fundamental Research Funds for the Central Universities
               [DUT24RC(3)118 to Law, J.; DUT25RC(3)040 to Du, X.].

               Conflicts of interest
               All authors declared that there are no conflicts of interest.


               Ethical approval and consent to participate
               Not applicable.

               Consent for publication
               Not applicable.

               Copyright
               © The Author(s) 2026.


               REFERENCES

               1.  Kim, S.; Laschi, C.; Trimmer, B. Soft robotics: a bioinspired evolution in robotics. Trends. Biotechnol. 2013, 31, 287-94. DOI PubMed
               2.  Yang, G. Z.; Fischer, P.; Nelson, B. New materials for next-generation robots. Sci. Robot. 2017, 2. DOI PubMed
               3.  Ranzani, T.; Russo, S.; Bartlett, N. W.; Wehner, M.; Wood, R. J. Increasing the dimensionality of soft microstructures through injection-
                  induced self-folding. Adv. Mater. 2018, 30, e1802739. DOI
               4.  Shen, Z.; Chen, F.; Zhu, X.; Yong, K. T.; Gu, G. Stimuli-responsive functional materials for soft robotics. J. Mater. Chem. B. 2020. DOI
                  PubMed
               5.  Lou, H.; Wang, Y.; Sheng, Y.; et al. Water-induced shape-locking magnetic robots. Adv. Sci. (Weinh). 2024, 11, e2405021. DOI PubMed
                  PMC
               6.  Rus, D.; Tolley, M. T. Design, fabrication and control of soft robots. Nature 2015, 521, 467-75. DOI PubMed
               7.  Laschi, C.; Mazzolai, B.; Cianchetti, M. Soft robotics: Technologies and systems pushing the boundaries of robot abilities. Sci. Robot.
                  2016, 1. DOI PubMed
               8.  Sitti, M. Miniature soft robots - road to the clinic. Nat. Rev. Mater. 2018, 3, 74-5. DOI
               9.  Kim, Y.; Zhao, X. Magnetic soft materials and robots. Chem. Rev. 2022, 122, 5317-64. DOI PubMed PMC
               10.  Tang, C.; Du, B.; Jiang, S.; et al. A pipeline inspection robot for navigating tubular environments in the sub-centimeter scale. Sci. Robot.
                  2022, 7, eabm8597. DOI PubMed
               11.  Cianchetti, M.; Laschi, C.; Menciassi, A.; Dario, P. Biomedical applications of soft robotics. Nat. Rev. Mater. 2018, 3, 143-53. DOI
               12.  Wang, T.; Wu, Y.; Yildiz, E.; Kanyas, S.; Sitti, M. Clinical translation of wireless soft robotic medical devices. Nat. Rev. Bioeng. 2024,
                  2, 470-85. DOI
               13.  Law, J.; Chen, H.; Wang, Y.; Yu, J.; Sun, Y. Gravity-resisting colloidal collectives. Sci. Adv. 2022, 8, eade3161. DOI PubMed PMC
   16   17   18   19   20   21   22   23   24   25   26