Recent Advances in Bioinspired Soft Robots: Fabrication, Actuation, Tracking, and Applications
Source abstract
Abstract
Abstract Natural organisms offer a rich source for the construction of soft robots exhibiting autonomous and intelligent behaviors, encompassing attributes like motion, perception, and adaptability to environmental shifts. Drawing inspiration from these biological models, a multitude of soft robots have emerged, each distinguished by unique structures and functionalities enabling diverse actions, including swimming, crawling, swinging, walking, and tumbling. In this review, several soft robots and their motion modes from the perspective of specific native species are addressed. The actuation methods of soft robots are discussed, encompassing chemical, electrical, ultrasonic, optical, and magnetic actuation mechanisms. Furthermore, the application domains of soft robots, encompassing areas such as vessel recanalization, targeted drug delivery, cargo manipulation, and sensing are explored, providing a concise summary of their roles and potentials. The current challenges encountered in this research field are highlighted, and promising directions pertaining to soft robots are emphasized.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Micro and Nano Robotics · Advanced Materials and Mechanics · Modular Robots and Swarm Intelligence
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Chemistry and Environmental Engineering Shenzhen University Shenzhen 518055 China
Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin New Territories Hong Kong SAR 999077 China
Multi‐Scale Medical Robotics Center Hong Kong Science Park Shatin New Territories Hong Kong SAR 999077 China
Funding
National Natural Science Foundation of China · Basic and Applied Basic Research Foundation of Guangdong Province
References (100+)
Show source-provided references
1. 10.1016/j.mattod.2022.01.01410.1016/j.mattod.2022.01.014 ↗
2. 10.1002/adma.20220067110.1002/adma.202200671 ↗
3. 10.1016/j.apmt.2022.10142310.1016/j.apmt.2022.101423 ↗
4. 10.1002/admt.20180047710.1002/admt.201800477 ↗
5. 10.1016/j.nantod.2023.10176410.1016/j.nantod.2023.101764 ↗
6. 10.1126/scirobotics.aax732910.1126/scirobotics.aax7329 ↗
7. 10.1126/sciadv.adk897010.1126/sciadv.adk8970 ↗
8. 10.1002/advs.20180158410.1002/advs.201801584 ↗
9. 10.1146/annurev-bioeng-071114-04063210.1146/annurev-bioeng-071114-040632 ↗
10. 10.1126/scirobotics.abd281310.1126/scirobotics.abd2813 ↗
11. 10.1126/scirobotics.abc880110.1126/scirobotics.abc8801 ↗
12. 10.1098/rsif.2017.010110.1098/rsif.2017.0101 ↗
13. 10.1002/aisy.20200014810.1002/aisy.202000148 ↗
14. 10.1021/acsnano.2c0471610.1021/acsnano.2c04716 ↗
15. 10.1002/adma.20200204710.1002/adma.202002047 ↗
16. 10.1002/aisy.20200028210.1002/aisy.202000282 ↗
17. 10.1073/pnas.200205911710.1073/pnas.2002059117 ↗
18. 10.1038/s41578-018-0002-210.1038/s41578-018-0002-2 ↗
19. 10.1038/s41578-018-0022-y10.1038/s41578-018-0022-y ↗
20. 10.1126/scirobotics.aav449410.1126/scirobotics.aav4494 ↗
21. 10.1002/adfm.20200513710.1002/adfm.202005137 ↗
22. 10.1016/j.mtcomm.2024.10830310.1016/j.mtcomm.2024.108303 ↗
23. 10.3390/biomimetics704020510.3390/biomimetics7040205 ↗
24. 10.1039/C7TB01605K10.1039/C7TB01605K ↗
25. 10.1038/s41467-018-06491-910.1038/s41467-018-06491-9 ↗
26. 10.1002/admt.20190033210.1002/admt.201900332 ↗
27. 10.1002/adfm.20191032310.1002/adfm.201910323 ↗
28. 10.1002/adfm.20221191810.1002/adfm.202211918 ↗
29. 10.1038/nature1910010.1038/nature19100 ↗
30. 10.1002/adma.20180273910.1002/adma.201802739 ↗
31. 10.1021/nn300413p10.1021/nn300413p ↗
32. 10.1038/ncomms1226310.1038/ncomms12263 ↗
33. Y.Dai T.Qu H.Zang C.Liu inWRC Symp. on Advanced Robotics and Automation (WRC SARA) IEEE Piscataway NJ2019 pp.228–234.10.1109/WRC-SARA.2019.8931804 ↗
34. 10.1002/adfm.20210344210.1002/adfm.202103442 ↗
35. 10.1126/scirobotics.aar442310.1126/scirobotics.aar4423 ↗
36. 10.1126/scirobotics.abd281310.1126/scirobotics.abd2813 ↗
37. 10.1021/acsnano.1c0665110.1021/acsnano.1c06651 ↗
38. 10.1126/scirobotics.aax711210.1126/scirobotics.aax7112 ↗
39. 10.1038/nchem.230310.1038/nchem.2303 ↗
40. 10.1021/jacs.8b1048110.1021/jacs.8b10481 ↗
41. 10.1039/C7CC00537G10.1039/C7CC00537G ↗
42. Charlesby A. · 2016
43. 10.1002/app.1964.07008043310.1002/app.1964.070080433 ↗
44. Charlesby A. · Radiat. Phys. Chem. · 1987 · 30 · 67
45. 10.1016/j.eurpolymj.2012.11.00110.1016/j.eurpolymj.2012.11.001 ↗
46. 10.1126/science.114559310.1126/science.1145593 ↗
47. 10.1021/ma071517z10.1021/ma071517z ↗
48. 10.1002/adfm.20120339610.1002/adfm.201203396 ↗
49. 10.1002/adfm.20180280910.1002/adfm.201802809 ↗
50. 10.1016/j.polymertesting.2020.10677410.1016/j.polymertesting.2020.106774 ↗
51. 10.1007/s42114-018-0072-z10.1007/s42114-018-0072-z ↗
52. 10.3390/polym303121510.3390/polym3031215 ↗
53. 10.1016/j.reactfunctpolym.2022.10539710.1016/j.reactfunctpolym.2022.105397 ↗
54. 10.1002/anie.20120954010.1002/anie.201209540 ↗
55. 10.1126/science.aab012910.1126/science.aab0129 ↗
56. 10.1089/soro.2014.002110.1089/soro.2014.0021 ↗
57. 10.1177/027836491140723110.1177/0278364911407231 ↗
58. 10.1126/sciadv.160204510.1126/sciadv.1602045 ↗
59. Najem J. · Proc. SPIE · 2012 · 8340 · 1
60. 10.1088/1748-3182/6/3/03600410.1088/1748-3182/6/3/036004 ↗
61. 10.1021/acsnano.8b0520310.1021/acsnano.8b05203 ↗
62. 10.1002/adma.20160482510.1002/adma.201604825 ↗
63. 10.1002/admt.20180054010.1002/admt.201800540 ↗
64. 10.1038/srep1741410.1038/srep17414 ↗
65. 10.1002/adom.20160050310.1002/adom.201600503 ↗
66. 10.1109/TBME.2013.228336910.1109/TBME.2013.2283369 ↗
67. 10.1002/adma.20230191610.1002/adma.202301916 ↗
68. 10.1126/scirobotics.aay262710.1126/scirobotics.aay2627 ↗
69. 10.1126/scirobotics.abc372110.1126/scirobotics.abc3721 ↗
70. Xu S. · Proc. Natl. Acad. Sci. USA · 2021 · 118
71. 10.3389/frobt.2021.68869710.3389/frobt.2021.688697 ↗
72. 10.1126/sciadv.aaz691210.1126/sciadv.aaz6912 ↗
73. 10.1002/admt.20220125910.1002/admt.202201259 ↗
74. 10.1002/ange.20181005210.1002/ange.201810052 ↗
75. 10.1002/marc.20170022410.1002/marc.201700224 ↗
76. 10.1038/nature2298710.1038/nature22987 ↗
77. 10.1038/s41467-019-12583-x10.1038/s41467-019-12583-x ↗
78. 10.1007/s42235-022-00296-910.1007/s42235-022-00296-9 ↗
79. 10.1038/s41467-020-16458-410.1038/s41467-020-16458-4 ↗
80. 10.1038/s41467-020-18214-010.1038/s41467-020-18214-0 ↗
81. 10.1002/adma.20160646710.1002/adma.201606467 ↗
82. 10.1002/adfm.20210182510.1002/adfm.202101825 ↗
83. 10.1038/s41467-018-06011-910.1038/s41467-018-06011-9 ↗
84. 10.1016/j.mattod.2021.04.01410.1016/j.mattod.2021.04.014 ↗
85. 10.1038/nature2544310.1038/nature25443 ↗
86. 10.1021/acs.nanolett.5b0192510.1021/acs.nanolett.5b01925 ↗
87. 10.1038/s41467-019-10549-710.1038/s41467-019-10549-7 ↗
88. 10.1089/soro.2018.002610.1089/soro.2018.0026 ↗
89. 10.3390/diagnostics204007210.3390/diagnostics2040072 ↗
90. Steager E. · IEEE Int. J. Rob. Autom. · 2012 · 3541
91. 10.1126/scirobotics.aaq115510.1126/scirobotics.aaq1155 ↗
92. 10.1006/abio.2000.500610.1006/abio.2000.5006 ↗
93. 10.1021/cr050019q10.1021/cr050019q ↗
94. 10.1089/adt.2016.70710.1089/adt.2016.707 ↗
95. 10.1158/1078-0432.CCR-08-320610.1158/1078-0432.CCR-08-3206 ↗
96. 10.1177/027836490810092410.1177/0278364908100924 ↗
97. 10.1063/1.240222110.1063/1.2402221 ↗
98. B.Behkam M.Sitti inProc. of 2005 IEEE/ASME Int. Conf. on Advanced Intelligent Mechatronics IEEE Piscataway NJ2005 pp.37–42.
99. A.Sanchez V.Magdanz O.Schmidt (Eds:S.Misra R. Carloni) 5th IEEE RAS & EMBS Int. Conf. on Biomedical Robotics and Biomechatronics (BioRob) IEEE Piscataway NJ2014 pp.169–174.10.1109/BIOROB.2014.6913771 ↗
100. 10.1016/j.biomaterials.2013.06.05510.1016/j.biomaterials.2013.06.055 ↗