{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T03:08:54Z","timestamp":1772248134889,"version":"3.50.1"},"reference-count":137,"publisher":"MIT Press - Journals","issue":"4","content-domain":{"domain":["direct.mit.edu"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,2,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>We introduce the framework of reality-assisted evolution to summarize a growing trend towards combining model-based and model-free approaches to improve the design of physically embodied soft robots. In silico, data-driven models build, adapt, and improve representations of the target system using real-world experimental data. By simulating huge numbers of virtual robots using these data-driven models, optimization algorithms can illuminate multiple design candidates for transference to the real world. In reality, large-scale physical experimentation facilitates the fabrication, testing, and analysis of multiple candidate designs. Automated assembly and reconfigurable modular systems enable significantly higher numbers of real-world design evaluations than previously possible. Large volumes of ground-truth data gathered via physical experimentation can be returned to the virtual environment to improve data-driven models and guide optimization. Grounding the design process in physical experimentation ensures that the complexity of virtual robot designs does not outpace the model limitations or available fabrication technologies. We outline key developments in the design of physically embodied soft robots in the framework of reality-assisted evolution.<\/jats:p>","DOI":"10.1162\/artl_a_00330","type":"journal-article","created":{"date-parts":[[2021,1,25]],"date-time":"2021-01-25T18:32:49Z","timestamp":1611599569000},"page":"484-506","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":33,"title":["Reality-Assisted Evolution of Soft Robots through Large-Scale Physical Experimentation: A Review"],"prefix":"10.1162","volume":"26","author":[{"given":"Toby","family":"Howison","sequence":"first","affiliation":[{"name":"University of Cambridge, Bio-Inspired Robotics Lab. th533@cam.ac.uk"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simon","family":"Hauser","sequence":"additional","affiliation":[{"name":"University of Cambridge, Bio-Inspired Robotics Lab."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Josie","family":"Hughes","sequence":"additional","affiliation":[{"name":"University of Cambridge, Bio-Inspired Robotics Lab."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fumiya","family":"Iida","sequence":"additional","affiliation":[{"name":"University of Cambridge, Bio-Inspired Robotics Lab."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"281","published-online":{"date-parts":[[2021,2,1]]},"reference":[{"key":"2021051117414369500_bib1","doi-asserted-by":"crossref","unstructured":"Alapan,  Y., Yasa,  O., Yigit,  B., Yasa,  I. C., Erkoc,  P., & Sitti,  M. (2019). Microrobotics and microorganisms: Biohybrid autonomous cellular robots. Annual Review of Control, Robotics, and Systems, 2(1), 205\u2013230. DOI: https:\/\/doi.org\/10.1146\/annurev-control-053018-023803","DOI":"10.1146\/annurev-control-053018-023803"},{"key":"2021051117414369500_bib2","doi-asserted-by":"crossref","unstructured":"Bowyer,  A.\n           (2014). 3D printing and humanity\u2019s first imperfect replicator. 3D Printing and Additive Manufacturing, 1(1), 4\u20135. DOI: https:\/\/doi.org\/10.1089\/3dp.2013.0003","DOI":"10.1089\/3dp.2013.0003"},{"key":"2021051117414369500_bib3","doi-asserted-by":"crossref","unstructured":"Brodbeck,  L., Hauser,  S., & Iida,  F. (2015). Morphological evolution of physical robots through model-free phenotype development. PLOS ONE, 10(6), e0128444. DOI: https:\/\/doi.org\/10.1371\/journal.pone.0128444, PMID: 26091255, PMCID: PMC4474803","DOI":"10.1371\/journal.pone.0128444"},{"key":"2021051117414369500_bib4","doi-asserted-by":"crossref","unstructured":"Brunton,  S. L., Proctor,  J. L., & Kutz,  J. N. (2016). Discovering governing equations from data by sparse identification of nonlinear dynamical systems. Proceedings of the National Academy of Sciences of the USA, 113(15), 3932\u20133937. DOI: https:\/\/doi.org\/10.1073\/pnas.1517384113, PMID: 27035946, PMCID: PMC4839439","DOI":"10.1073\/pnas.1517384113"},{"key":"2021051117414369500_bib5","doi-asserted-by":"crossref","unstructured":"Caluwaerts,  K., Despraz,  J., I\u015f\u00e7en,  A., Sabelhaus,  A. P., Bruce,  J., Schrauwen,  B., & SunSpiral,  V. (2014). Design and control of compliant tensegrity robots through simulation and hardware validation. Journal of The Royal Society Interface, 11(98), 20140520. DOI: https:\/\/doi.org\/10.1098\/rsif.2014.0520, PMID: 24990292, PMCID: PMC4233701","DOI":"10.1098\/rsif.2014.0520"},{"key":"2021051117414369500_bib6","doi-asserted-by":"crossref","unstructured":"Camarillo,  D. B., Milne,  C. F., Carlson,  C. R., Zinn,  M. R., & Salisbury,  J. K. (2008). Mechanics modeling of tendon-driven continuum manipulators. IEEE Transactions on Robotics, 24(6), 1262\u20131273. DOI: https:\/\/doi.org\/10.1109\/TRO.2008.2002311","DOI":"10.1109\/TRO.2008.2002311"},{"key":"2021051117414369500_bib7","doi-asserted-by":"crossref","unstructured":"Cellucci,  D., MacCurdy,  R., Lipson,  H., & Risi,  S. (2017). 1D printing of recyclable robots. IEEE Robotics and Automation Letters, 2(4), 1964\u20131971. DOI: https:\/\/doi.org\/10.1109\/LRA.2017.2716418","DOI":"10.1109\/LRA.2017.2716418"},{"key":"2021051117414369500_bib8","doi-asserted-by":"crossref","unstructured":"Cheney,  N., Bongard,  J., & Lipson,  H. (2015). Evolving soft robots in tight spaces. In Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation (pp. 935\u2013942). New York: ACM. DOI: https:\/\/doi.org\/10.1145\/2739480.2754662","DOI":"10.1145\/2739480.2754662"},{"key":"2021051117414369500_bib9","doi-asserted-by":"crossref","unstructured":"Cheney,  N., MacCurdy,  R., Clune,  J., & Lipson,  H. (2013). Unshackling evolution: Evolving soft robots with multiple materials and a powerful generative encoding. In Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation (pp. 167\u2013174). New York: ACM.","DOI":"10.1145\/2463372.2463404"},{"key":"2021051117414369500_bib10","doi-asserted-by":"crossref","unstructured":"Choi,  C., Schwarting,  W., DelPreto,  J., & Rus,  D. (2018). Learning object grasping for soft robot hands. IEEE Robotics and Automation Letters, 3(3), 2370\u20132377. DOI: https:\/\/doi.org\/10.1109\/LRA.2018.2810544","DOI":"10.1109\/LRA.2018.2810544"},{"key":"2021051117414369500_bib11","doi-asserted-by":"crossref","unstructured":"Chossat,  J., Park,  Y., Wood,  R. J., & Duchaine,  V. (2013). A soft strain sensor based on ionic and metal liquids. IEEE Sensors Journal, 13(9), 3405\u20133414. DOI: https:\/\/doi.org\/10.1109\/JSEN.2013.2263797","DOI":"10.1109\/JSEN.2013.2263797"},{"key":"2021051117414369500_bib12","doi-asserted-by":"crossref","unstructured":"Cira,  N. J., Benusiglio,  A., & Prakash,  M. (2015). Vapour-mediated sensing and motility in two-component droplets. Nature, 519(7544), 446\u2013450. DOI: https:\/\/doi.org\/10.1038\/nature14272, PMID: 25762146","DOI":"10.1038\/nature14272"},{"key":"2021051117414369500_bib13","doi-asserted-by":"crossref","unstructured":"Clark,  A.\n           (2008). Supersizing the mind: Embodiment, action, and cognitive extension. Oxford, UK: Oxford University Press. DOI: https:\/\/doi.org\/10.1093\/acprof:oso\/9780195333213.001.0001","DOI":"10.1093\/acprof:oso\/9780195333213.001.0001"},{"key":"2021051117414369500_bib14","doi-asserted-by":"crossref","unstructured":"Clune,  J., Mouret,  J.-B., & Lipson,  H. (2013). The evolutionary origins of modularity. Proceedings of the Royal Society B: Biological Sciences, 280(1755), 20122863. DOI: https:\/\/doi.org\/10.1098\/rspb.2012.2863, PMID: 23363632, PMCID: PMC3574393","DOI":"10.1098\/rspb.2012.2863"},{"key":"2021051117414369500_bib15","doi-asserted-by":"crossref","unstructured":"Clune,  J., Stanley,  K. O., Pennock,  R. T., & Ofria,  C. (2011). On the performance of indirect encoding across the continuum of regularity. IEEE Transactions on Evolutionary Computation, 15(3), 346\u2013367. DOI: https:\/\/doi.org\/10.1109\/TEVC.2010.2104157","DOI":"10.1109\/TEVC.2010.2104157"},{"key":"2021051117414369500_bib16","doi-asserted-by":"crossref","unstructured":"Connolly,  F., Polygerinos,  P., Walsh,  C. J., & Bertoldi,  K. (2015). Mechanical programming of soft actuators by varying fiber angle. Soft Robotics, 2(1), 26\u201332. DOI: https:\/\/doi.org\/10.1089\/soro.2015.0001","DOI":"10.1089\/soro.2015.0001"},{"key":"2021051117414369500_bib17","doi-asserted-by":"crossref","unstructured":"Corucci,  F., Calisti,  M., Hauser,  H., & Laschi,  C. (2015). Novelty-based evolutionary design of morphing underwater robots. In Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation (pp. 145\u2013152). New York: ACM. DOI: https:\/\/doi.org\/10.1145\/2739480.2754686","DOI":"10.1145\/2739480.2754686"},{"key":"2021051117414369500_bib18","doi-asserted-by":"crossref","unstructured":"Corucci,  F., Cheney,  N., Giorgio-Serchi,  F., Bongard,  J., & Laschi,  C. (2018). Evolving soft locomotion in aquatic and terrestrial environments: Effects of material properties and environmental transitions. Soft Robotics, 5(4), 475\u2013495. DOI: https:\/\/doi.org\/10.1089\/soro.2017.0055, PMID: 29985740","DOI":"10.1089\/soro.2017.0055"},{"key":"2021051117414369500_bib19","doi-asserted-by":"crossref","unstructured":"Cully,  A., Clune,  J., Tarapore,  D., & Mouret,  J.-B. (2015). Robots that can adapt like animals. Nature, 521(7553), 503\u2013507. DOI: https:\/\/doi.org\/10.1038\/nature14422, PMID: 26017452","DOI":"10.1038\/nature14422"},{"key":"2021051117414369500_bib20","doi-asserted-by":"crossref","unstructured":"Davey,  J., Kwok,  N., & Yim,  M. (2012). Emulating self-reconfigurable robots\u2014design of the SMORES system. In 2012 IEEE\/RSJ International Conference on Intelligent Robots and Systems (pp. 4464\u20134469). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/IROS.2012.6385845","DOI":"10.1109\/IROS.2012.6385845"},{"key":"2021051117414369500_bib21","doi-asserted-by":"crossref","unstructured":"Doncieux,  S., Laflaqu\u00ecere,  A., & Coninx,  A. (2019). Novelty search: A theoretical perspective. In Proceedings of the Genetic and Evolutionary Computation Conference (pp. 99\u2013106). New York: ACM. DOI: https:\/\/doi.org\/10.1145\/3321707.3321752","DOI":"10.1145\/3321707.3321752"},{"key":"2021051117414369500_bib22","doi-asserted-by":"crossref","unstructured":"Doursat,  R., & S\u00e1nchez,  C. (2014). Growing fine-grained multicellular robots. Soft Robotics, 1(2), 110\u2013121. DOI: https:\/\/doi.org\/10.1089\/soro.2014.0014","DOI":"10.1089\/soro.2014.0014"},{"key":"2021051117414369500_bib23","doi-asserted-by":"crossref","unstructured":"Drotman,  D., Jadhav,  S., Karimi,  M., de Zonia,  P., & Tolley,  M. T. (2017). 3D printed soft actuators for a legged robot capable of navigating unstructured terrain. In 2017 IEEE International Conference on Robotics and Automation (ICRA) (pp. 5532\u20135538). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/ICRA.2017.7989652","DOI":"10.1109\/ICRA.2017.7989652"},{"key":"2021051117414369500_bib24","doi-asserted-by":"crossref","unstructured":"Duarte,  M., Gomes,  J., Oliveira,  S. M., & Christensen,  A. L. (2018). Evolution of repertoire-based control for robots with complex locomotor systems. IEEE Transactions on Evolutionary Computation, 22(2), 314\u2013328. DOI: https:\/\/doi.org\/10.1109\/TEVC.2017.2722101","DOI":"10.1109\/TEVC.2017.2722101"},{"key":"2021051117414369500_bib25","doi-asserted-by":"crossref","unstructured":"Duriez,  C.\n           (2013). Control of elastic soft robots based on real-time finite element method. In 2013 IEEE International Conference on Robotics and Automation (pp. 3982\u20133987). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/ICRA.2013.6631138","DOI":"10.1109\/ICRA.2013.6631138"},{"key":"2021051117414369500_bib26","doi-asserted-by":"crossref","unstructured":"Eiben,  A., Bredeche,  N., Hoogendoorn,  M., Stradner,  J., Timmis,  J., Tyrrell,  A., & Winfield,  A. (2013). The triangle of life: Evolving robots in real-time and real-space. In ECAL 2013: The Twelfth European Conference on Artificial Life (pp. 1056\u20131063). Cambridge, MA: MIT Press. DOI: https:\/\/doi.org\/10.7551\/978-0-262-31709-2-ch157","DOI":"10.7551\/978-0-262-31709-2-ch157"},{"key":"2021051117414369500_bib27","doi-asserted-by":"crossref","unstructured":"Firouzeh,  A., Amon-Junior,  A. F., & Paik,  J. (2015). Soft piezoresistive sensor model and characterization with varying design parameters. Sensors and Actuators A: Physical, 233, 158\u2013168. DOI: https:\/\/doi.org\/10.1016\/j.sna.2015.06.007","DOI":"10.1016\/j.sna.2015.06.007"},{"key":"2021051117414369500_bib28","unstructured":"Frazier,  P. I.\n           (2018). A tutorial on Bayesian optimization. arXiv Preprint arXiv:1807.02811."},{"key":"2021051117414369500_bib29","doi-asserted-by":"crossref","unstructured":"Frutiger,  A., Muth,  J. T., Vogt,  D. M., Meng\u00fc\u00e7,  Y., Campo,  A., Valentine,  A. D., Walsh,  C. J., & Lewis,  J. A. (2015). Capacitive soft strain sensors via multicore\u2013shell fiber printing. Advanced Materials, 27(15), 2440\u20132446. DOI: https:\/\/doi.org\/10.1002\/adma.201500072, PMID: 25754237","DOI":"10.1002\/adma.201500072"},{"key":"2021051117414369500_bib30","doi-asserted-by":"crossref","unstructured":"Gilday,  K., Thuruthel,  T. G., & Iida,  F. (2020). A vision-based collocated actuation-sensing scheme for a compliant tendon-driven robotic hand. In 2020 3rd IEEE International Conference on Soft Robotics (RoboSoft) (pp. 760\u2013765). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/RoboSoft48309.2020.9116054","DOI":"10.1109\/RoboSoft48309.2020.9116054"},{"key":"2021051117414369500_bib31","doi-asserted-by":"crossref","unstructured":"Gilpin,  K., Knaian,  A., & Rus,  D. (2010). Robot pebbles: One centimeter modules for programmable matter through self-disassembly. In 2010 IEEE International Conference on Robotics and Automation (pp. 2485\u20132492). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/ROBOT.2010.5509817","DOI":"10.1109\/ROBOT.2010.5509817"},{"key":"2021051117414369500_bib32","doi-asserted-by":"crossref","unstructured":"Gilpin,  K., Kotay,  K., Rus,  D., & Vasilescu,  I. (2008). Miche: Modular shape formation by self-disassembly. The International Journal of Robotics Research, 27(3\u20134), 345\u2013372. DOI: https:\/\/doi.org\/10.1177\/0278364907085557","DOI":"10.1177\/0278364907085557"},{"key":"2021051117414369500_bib33","doi-asserted-by":"crossref","unstructured":"Giorelli,  M., Renda,  F., Calisti,  M., Arienti,  A., Ferri,  G., & Laschi,  C. (2015). Neural network and Jacobian method for solving the inverse statics of a cable-driven soft arm with nonconstant curvature. IEEE Transactions on Robotics, 31(4), 823\u2013834. DOI: https:\/\/doi.org\/10.1109\/TRO.2015.2428511","DOI":"10.1109\/TRO.2015.2428511"},{"key":"2021051117414369500_bib34","doi-asserted-by":"crossref","unstructured":"Gu,  G.-Y., Zhu,  J., Zhu,  L.-M., & Zhu,  X. (2017). A survey on dielectric elastomer actuators for soft robots. Bioinspiration & Biomimetics, 12(1), 011003. DOI: https:\/\/doi.org\/10.1088\/1748-3190\/12\/1\/011003, PMID: 28114111","DOI":"10.1088\/1748-3190\/12\/1\/011003"},{"key":"2021051117414369500_bib35","doi-asserted-by":"crossref","unstructured":"Gul,  J. Z., Sajid,  M., Rehman,  M. M., Siddiqui,  G. U., Shah,  I., Kim,  K.-H., Lee,  J.-W., & Choi,  K. H. (2018). 3D printing for soft robotics\u2014a review. Science and Technology of Advanced Materials, 19(1), 243\u2013262. DOI: https:\/\/doi.org\/10.1080\/14686996.2018.1431862, PMID: 29707065, PMCID: PMC5917433","DOI":"10.1080\/14686996.2018.1431862"},{"key":"2021051117414369500_bib36","doi-asserted-by":"crossref","unstructured":"Hauser,  S., Mutlu,  M., L\u00e9ziart,  P. A., Khodr,  H., Bernardino,  A., & Ijspeert,  A. J. (2020). Roombots extended: Challenges in the next generation of self-reconfigurable modular robots and their application in adaptive and assistive furniture. Robotics and Autonomous Systems, 127, 103467. DOI: https:\/\/doi.org\/10.1016\/j.robot.2020.103467","DOI":"10.1016\/j.robot.2020.103467"},{"key":"2021051117414369500_bib37","doi-asserted-by":"crossref","unstructured":"Hawkes,  E. W., Blumenschein,  L. H., Greer,  J. D., & Okamura,  A. M. (2017). A soft robot that navigates its environment through growth. Science Robotics, 2(8), eaan3028. DOI: https:\/\/doi.org\/10.1126\/scirobotics.aan3028, PMID: 33157883","DOI":"10.1126\/scirobotics.aan3028"},{"key":"2021051117414369500_bib38","doi-asserted-by":"crossref","unstructured":"Hiller,  J., & Lipson,  H. (2012). Automatic design and manufacture of soft robots. IEEE Transactions on Robotics, 28(2), 457\u2013466. DOI: https:\/\/doi.org\/10.1109\/TRO.2011.2172702","DOI":"10.1109\/TRO.2011.2172702"},{"key":"2021051117414369500_bib39","doi-asserted-by":"crossref","unstructured":"Hiller,  J., & Lipson,  H. (2014). Dynamic simulation of soft multimaterial 3D-printed objects. Soft Robotics, 1(1), 88\u2013101. DOI: https:\/\/doi.org\/10.1089\/soro.2013.0010","DOI":"10.1089\/soro.2013.0010"},{"key":"2021051117414369500_bib40","unstructured":"Hornby,  G. S., & Pollack,  J. B. (2001). The advantages of generative grammatical encodings for physical design. In Proceedings of the 2001 Congress on Evolutionary Computation, Volume 1 (pp. 600\u2013607). New York: IEEE."},{"key":"2021051117414369500_bib41","doi-asserted-by":"crossref","unstructured":"Howard,  D., Eiben,  A. E., Kennedy,  D. F., Mouret,  J.-B., Valencia,  P., & Winkler,  D. (2019). Evolving embodied intelligence from materials to machines. Nature Machine Intelligence, 1(1), 12\u201319. DOI: https:\/\/doi.org\/10.1038\/s42256-018-0009-9","DOI":"10.1038\/s42256-018-0009-9"},{"key":"2021051117414369500_bib42","doi-asserted-by":"crossref","unstructured":"Howison,  T., Hughes,  J., & Iida,  F. (2020). Large-scale automated investigation of free-falling paper shapes via iterative physical experimentation. Nature Machine Intelligence, 2(1), 68\u201375. DOI: https:\/\/doi.org\/10.1038\/s42256-019-0135-z","DOI":"10.1038\/s42256-019-0135-z"},{"key":"2021051117414369500_bib43","doi-asserted-by":"crossref","unstructured":"Howison,  T., Hughes,  J., & Iida,  F. (2020). Morphologically programming the interactions of V-shaped falling papers. In ALIFE 2020: The 2020 Conference on Artificial Life (pp. 359\u2013366). Cambridge, MA: MIT Press. DOI: https:\/\/doi.org\/10.1162\/isal_a_00306","DOI":"10.1162\/isal_a_00306"},{"key":"2021051117414369500_bib44","doi-asserted-by":"crossref","unstructured":"Hu,  Y., Liu,  J., Spielberg,  A., Tenenbaum,  J. B., Freeman,  W. T., Wu,  J., Rus,  D., & Matusik,  W. (2019). ChainQueen: A real-time differentiable physical simulator for soft robotics. In 2019 International Conference on Robotics and Automation (ICRA) (pp. 6265\u20136271). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/ICRA.2019.8794333","DOI":"10.1109\/ICRA.2019.8794333"},{"key":"2021051117414369500_bib45","doi-asserted-by":"crossref","unstructured":"Hughes,  J., & Iida,  F. (2017). 3D printed sensorized soft robotic manipulator design. In Y.Gao, S.Fallah, Y.Jin, & C.Lekakou (Eds.), Towards autonomous robotic systems (pp. 627\u2013636). Cham: Springer. DOI: https:\/\/doi.org\/10.1007\/978-3-319-64107-2_51","DOI":"10.1007\/978-3-319-64107-2_51"},{"key":"2021051117414369500_bib46","doi-asserted-by":"crossref","unstructured":"Hughes,  J. A. E., Maiolino,  P., & Iida,  F. (2018). An anthropomorphic soft skeleton hand exploiting conditional models for piano playing. Science Robotics, 3(25), eaau3098. DOI: https:\/\/doi.org\/10.1126\/scirobotics.aau3098, PMID: 33141692","DOI":"10.1126\/scirobotics.aau3098"},{"key":"2021051117414369500_bib47","doi-asserted-by":"crossref","unstructured":"Huizinga,  J., Stanley,  K. O., & Clune,  J. (2018). The emergence of canalization and evolvability in an open-ended, interactive evolutionary system. Artificial Life, 24(3), 157\u2013181. DOI: https:\/\/doi.org\/10.1162\/artl_a_00263, PMID: 30485140","DOI":"10.1162\/artl_a_00263"},{"key":"2021051117414369500_bib48","doi-asserted-by":"crossref","unstructured":"Ilievski,  F., Mazzeo,  A. D., Shepherd,  R. F., Chen,  X., & Whitesides,  G. M. (2011). Soft robotics for chemists. Angewandte Chemie International Edition, 50(8), 1890\u20131895. DOI: https:\/\/doi.org\/10.1002\/anie.201006464, PMID: 21328664","DOI":"10.1002\/anie.201006464"},{"key":"2021051117414369500_bib49","doi-asserted-by":"crossref","unstructured":"Jacob,  C.\n           (1994). Genetic L-system programming. In Y.Davidor, H.-P.Schwefel, & R.M\u00e4nner (Eds.), Parallel problem solving from nature (pp. 333\u2013343). Berlin, Heidelberg: Springer. DOI: https:\/\/doi.org\/10.1007\/3-540-58484-6_277","DOI":"10.1007\/3-540-58484-6_277"},{"key":"2021051117414369500_bib50","doi-asserted-by":"crossref","unstructured":"Jakobi,  N.\n           (1997). Evolutionary robotics and the radical envelope-of-noise hypothesis. Adaptive Behavior, 6(2), 325\u2013368. DOI: https:\/\/doi.org\/10.1177\/105971239700600205","DOI":"10.1177\/105971239700600205"},{"key":"2021051117414369500_bib51","doi-asserted-by":"crossref","unstructured":"Joachimczak,  M., Suzuki,  R., & Arita,  T. (2015). Improving evolvability of morphologies and controllers of developmental soft-bodied robots with novelty search. Frontiers in Robotics and AI, 2, 33. DOI: https:\/\/doi.org\/10.3389\/frobt.2015.00033","DOI":"10.3389\/frobt.2015.00033"},{"key":"2021051117414369500_bib52","doi-asserted-by":"crossref","unstructured":"Katzschmann,  R. K., Marchese,  A. D., & Rus,  D. (2016). Hydraulic autonomous soft robotic fish for 3D swimming. In M. A.Hsieh, O.Khatib, & V.Kumar (Eds.), Experimental robotics: The 14th International Symposium on Experimental Robotics (pp. 405\u2013420). Cham: Springer. DOI: https:\/\/doi.org\/10.1007\/978-3-319-23778-7_27","DOI":"10.1007\/978-3-319-23778-7_27"},{"key":"2021051117414369500_bib53","doi-asserted-by":"crossref","unstructured":"Khazanov,  M., Jocque,  J., & Rieffel,  J. (2014). Evolution of locomotion on a physical tensegrity robot. In ALIFE 14: The Fourteenth International Conference on the Synthesis and Simulation of Living Systems (pp. 232\u2013238). Cambridge, MA: MIT Press.","DOI":"10.7551\/978-0-262-32621-6-ch039"},{"key":"2021051117414369500_bib54","doi-asserted-by":"crossref","unstructured":"Kim,  S., Laschi,  C., & Trimmer,  B. (2013). Soft robotics: A bioinspired evolution in robotics. Trends in Biotechnology, 31(5), 287\u2013294. DOI: https:\/\/doi.org\/10.1016\/j.tibtech.2013.03.002, PMID: 23582470","DOI":"10.1016\/j.tibtech.2013.03.002"},{"key":"2021051117414369500_bib55","doi-asserted-by":"crossref","unstructured":"Koos,  S., Mouret,  J., & Doncieux,  S. (2013). The transferability approach: Crossing the reality gap in evolutionary robotics. IEEE Transactions on Evolutionary Computation, 17(1), 122\u2013145. DOI: https:\/\/doi.org\/10.1109\/TEVC.2012.2185849","DOI":"10.1109\/TEVC.2012.2185849"},{"key":"2021051117414369500_bib56","doi-asserted-by":"crossref","unstructured":"Kriegman,  S., Blackiston,  D., Levin,  M., & Bongard,  J. (2020). A scalable pipeline for designing reconfigurable organisms. Proceedings of the National Academy of Sciences of the USA, 117(4), 1853\u20131859. DOI: https:\/\/doi.org\/10.1073\/pnas.1910837117, PMID: 31932426, PMCID: PMC6994979","DOI":"10.1073\/pnas.1910837117"},{"key":"2021051117414369500_bib57","doi-asserted-by":"crossref","unstructured":"Kriegman,  S., Cappelle,  C., Corucci,  F., Bernatskiy,  A., Cheney,  N., & Bongard,  J. C. (2017). Simulating the evolution of soft and rigid-body robots. In Proceedings of the Genetic and Evolutionary Computation Conference companion (pp. 1117\u20131120). New York: ACM. DOI: https:\/\/doi.org\/10.1145\/3067695.3082051","DOI":"10.1145\/3067695.3082051"},{"key":"2021051117414369500_bib58","doi-asserted-by":"crossref","unstructured":"Kriegman,  S., Cheney,  N., & Bongard,  J. (2018). How morphological development can guide evolution. Scientific Reports, 8(1), 1\u201310. DOI: https:\/\/doi.org\/10.1038\/s41598-018-31868-7, PMID: 30224743, PMCID: PMC6141532","DOI":"10.1038\/s41598-018-31868-7"},{"key":"2021051117414369500_bib59","doi-asserted-by":"crossref","unstructured":"Kriegman,  S., Nasab,  A. M., Shah,  D., Steele,  H., Branin,  G., Levin,  M., Bongard,  J., & Kramer-Bottiglio,  R. (2020). Scalable sim-to-real transfer of soft robot designs. In 2020 3rd IEEE International Conference on Soft Robotics (RoboSoft) (pp. 359\u2013366). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/RoboSoft48309.2020.9116004","DOI":"10.1109\/RoboSoft48309.2020.9116004"},{"key":"2021051117414369500_bib60","doi-asserted-by":"crossref","unstructured":"Kwiatkowski,  R., & Lipson,  H. (2019). Task-agnostic self-modeling machines. Science Robotics, 4(26), eaau9354. DOI: https:\/\/doi.org\/10.1126\/scirobotics.aau9354, PMID: 33137761","DOI":"10.1126\/scirobotics.aau9354"},{"key":"2021051117414369500_bib61","doi-asserted-by":"crossref","unstructured":"Laschi,  C., Mazzolai,  B., & Cianchetti,  M. (2016). Soft robotics: Technologies and systems pushing the boundaries of robot abilities. Science Robotics, 1(1), aah3690. DOI: https:\/\/doi.org\/10.1126\/scirobotics.aah3690, PMID: 33157856","DOI":"10.1126\/scirobotics.aah3690"},{"key":"2021051117414369500_bib62","doi-asserted-by":"crossref","unstructured":"Lau,  M., Ohgawara,  A., Mitani,  J., & Igarashi,  T. (2011). Converting 3D furniture models to fabricatable parts and connectors. ACM Transactions on Graphics, 30(4), 1\u20136. DOI: https:\/\/doi.org\/10.1145\/2010324.1964980","DOI":"10.1145\/2010324.1964980"},{"key":"2021051117414369500_bib63","doi-asserted-by":"crossref","unstructured":"Lehman,  J., & Miikkulainen,  R. (2015). Enhancing divergent search through extinction events. In Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation (pp. 951\u2013958). New York: ACM. DOI: https:\/\/doi.org\/10.1145\/2739480.2754668","DOI":"10.1145\/2739480.2754668"},{"key":"2021051117414369500_bib64","doi-asserted-by":"crossref","unstructured":"Lehman,  J., & Stanley,  K. O. (2011). Abandoning objectives: Evolution through the search for novelty alone. Evolutionary Computation, 19(2), 189\u2013223. DOI: https:\/\/doi.org\/10.1162\/EVCO_a_00025, PMID: 20868264","DOI":"10.1162\/EVCO_a_00025"},{"key":"2021051117414369500_bib65","doi-asserted-by":"crossref","unstructured":"Lehman,  J., & Stanley,  K. O. (2011). Evolving a diversity of virtual creatures through novelty search and local competition. In Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation (pp. 211\u2013218). New York: ACM. DOI: https:\/\/doi.org\/10.1145\/2001576.2001606","DOI":"10.1145\/2001576.2001606"},{"key":"2021051117414369500_bib66","doi-asserted-by":"crossref","unstructured":"Li,  J., Liu,  L., Liu,  Y., & Leng,  J. (2019). Dielectric elastomer spring-roll bending actuators: Applications in soft robotics and design. Soft Robotics, 6(1), 69\u201381. DOI: https:\/\/doi.org\/10.1089\/soro.2018.0037, PMID: 30335571","DOI":"10.1089\/soro.2018.0037"},{"key":"2021051117414369500_bib67","unstructured":"Liang,  J., Lin,  M., & Koltun,  V. (2019). Differentiable cloth simulation for inverse problems. In H.Wallach, H.Larochelle, A.Beygelzimer, F.dAlch\u00e9 Buc, E.Fox, & R.Garnett (Eds.), Advances in Neural Information Processing Systems 32 (pp. 772\u2013781). Red Hook, NY: Curran Associates Inc."},{"key":"2021051117414369500_bib68","doi-asserted-by":"crossref","unstructured":"Lipson,  H.\n           (2014). Challenges and opportunities for design, simulation, and fabrication of soft robots. Soft Robotics, 1(1), 21\u201327. DOI: https:\/\/doi.org\/10.1089\/soro.2013.0007","DOI":"10.1089\/soro.2013.0007"},{"key":"2021051117414369500_bib69","doi-asserted-by":"crossref","unstructured":"Lipton,  J. I., MacCurdy,  R., Manchester,  Z., Chin,  L., Cellucci,  D., & Rus,  D. (2018). Handedness in shearing auxetics creates rigid and compliant structures. Science, 360(6389), 632\u2013635. DOI: https:\/\/doi.org\/10.1126\/science.aar4586, PMID: 29748279","DOI":"10.1126\/science.aar4586"},{"key":"2021051117414369500_bib70","doi-asserted-by":"crossref","unstructured":"Malley,  M., Rubenstein,  M., & Nagpal,  R. (2017). Flippy: A soft, autonomous climber with simple sensing and control. In 2017 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 6533\u20136540). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/IROS.2017.8206563","DOI":"10.1109\/IROS.2017.8206563"},{"key":"2021051117414369500_bib71","doi-asserted-by":"crossref","unstructured":"Maziz,  A., Concas,  A., Khaldi,  A., St\u00e5lhand,  J., Persson,  N.-K., & Jager,  E. W. H. (2017). Knitting and weaving artificial muscles. Science Advances, 3(1), e1600327. DOI: https:\/\/doi.org\/10.1126\/sciadv.1600327, PMID: 28138542, PMCID: PMC5266480","DOI":"10.1126\/sciadv.1600327"},{"key":"2021051117414369500_bib72","unstructured":"McCormack,  J., Dorin,  A., & Innocent,  T. (2005). Generative design: A paradigm for design research. In J.Redmond, D.Durling, & A.de Bono (Eds.), Futureground, volume 2. Melbourne: Monash University."},{"key":"2021051117414369500_bib73","doi-asserted-by":"crossref","unstructured":"Mehta,  A. M., DelPreto,  J., Shaya,  B., & Rus,  D. (2014). Cogeneration of mechanical, electrical, and software designs for printable robots from structural specifications. In 2014 IEEE\/RSJ International Conference on Intelligent Robots and Systems (pp. 2892\u20132897). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/IROS.2014.6942960","DOI":"10.1109\/IROS.2014.6942960"},{"key":"2021051117414369500_bib74","doi-asserted-by":"crossref","unstructured":"Mehta,  A. M., & Rus,  D. (2014). An end-to-end system for designing mechanical structures for print-and-fold robots. In 2014 IEEE International Conference on Robotics and Automation (ICRA) (pp. 1460\u20131465). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/ICRA.2014.6907044","DOI":"10.1109\/ICRA.2014.6907044"},{"key":"2021051117414369500_bib75","doi-asserted-by":"crossref","unstructured":"Morimoto,  Y., Onoe,  H., & Takeuchi,  S. (2018). Biohybrid robot powered by an antagonistic pair of skeletal muscle tissues. Science Robotics, 3(18), eaat4440. DOI: https:\/\/doi.org\/10.1126\/scirobotics.aat4440, PMID: 33141706","DOI":"10.1126\/scirobotics.aat4440"},{"key":"2021051117414369500_bib76","doi-asserted-by":"crossref","unstructured":"Motzki,  P., Khelfa,  F., Zimmer,  L., Schmidt,  M., & Seelecke,  S. (2019). Design and validation of a reconfigurable robotic end-effector based on shape memory alloys. IEEE\/ASME Transactions on Mechatronics, 24(1), 293\u2013303. DOI: https:\/\/doi.org\/10.1109\/TMECH.2019.2891348","DOI":"10.1109\/TMECH.2019.2891348"},{"key":"2021051117414369500_bib77","doi-asserted-by":"crossref","unstructured":"Mouret,  J.-B., & Chatzilygeroudis,  K. (2017). 20 years of reality gap: A few thoughts about simulators in evolutionary robotics. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 1121\u20131124). New York: ACM. DOI: https:\/\/doi.org\/10.1145\/3067695.3082052","DOI":"10.1145\/3067695.3082052"},{"key":"2021051117414369500_bib78","unstructured":"Mouret,  J.-B., & Clune,  J. (2015). Illuminating search spaces by mapping elites. arXiv Preprint arXiv:1504.04909."},{"key":"2021051117414369500_bib79","doi-asserted-by":"crossref","unstructured":"Mouret,  J.-B., & Doncieux,  S. (2008). Incremental evolution of animats\u2019 behaviors as a multi-objective optimization. In M.Asada, J. C. T.Hallam, J.-A.Meyer, & J.Tani (Eds.), From Animals to Animats 10 (pp. 210\u2013219). Berlin, Heidelberg: Springer. DOI: https:\/\/doi.org\/10.1007\/978-3-540-69134-1_21","DOI":"10.1007\/978-3-540-69134-1_21"},{"key":"2021051117414369500_bib80","doi-asserted-by":"crossref","unstructured":"Mouret,  J.-B., & Doncieux,  S. (2012). Encouraging behavioral diversity in evolutionary robotics: An empirical study. Evolutionary Computation, 20(1), 91\u2013133. DOI: https:\/\/doi.org\/10.1162\/EVCO_a_00048, PMID: 21838553","DOI":"10.1162\/EVCO_a_00048"},{"key":"2021051117414369500_bib81","doi-asserted-by":"crossref","unstructured":"Nakajima,  K., Hauser,  H., Li,  T., & Pfeifer,  R. (2015). Information processing via physical soft body. Scientific Reports, 5, 10487. DOI: https:\/\/doi.org\/10.1038\/srep10487, PMID: 26014748, PMCID: PMC4444959","DOI":"10.1038\/srep10487"},{"key":"2021051117414369500_bib82","doi-asserted-by":"crossref","unstructured":"Neubert,  J., & Lipson,  H. (2015). Soldercubes: A self-soldering self-reconfiguring modular robot system. Autonomous Robots, 40, 139\u2013158. DOI: https:\/\/doi.org\/10.1007\/s10514-015-9441-4","DOI":"10.1007\/s10514-015-9441-4"},{"key":"2021051117414369500_bib83","doi-asserted-by":"crossref","unstructured":"Nurzaman,  S. G., Culha,  U., Brodbeck,  L., Wang,  L., & Iida,  F. (2013). Active sensing system with in situ adjustable sensor morphology. PLOS ONE, 8(12), e84090. DOI: https:\/\/doi.org\/10.1371\/journal.pone.0084090, PMID: 24416094, PMCID: PMC3887119","DOI":"10.1371\/journal.pone.0084090"},{"key":"2021051117414369500_bib84","doi-asserted-by":"crossref","unstructured":"Nurzaman,  S. G., Iida,  F., Margheri,  L., & Laschi,  C. (2014). Soft robotics on the move: Scientific networks, activities, and future challenges. Soft Robotics, 1, 154\u2013158. DOI: https:\/\/doi.org\/10.1089\/soro.2014.0012","DOI":"10.1089\/soro.2014.0012"},{"key":"2021051117414369500_bib85","doi-asserted-by":"crossref","unstructured":"Nygaard,  T. F., Martin,  C. P., Samuelsen,  E., Torresen,  J., & Glette,  K. (2018). Real-world evolution adapts robot morphology and control to hardware limitations. In Proceedings of the Genetic and Evolutionary Computation Conference (pp. 125\u2013132). New York: ACM. DOI: https:\/\/doi.org\/10.1145\/3205455.3205567","DOI":"10.1145\/3205455.3205567"},{"key":"2021051117414369500_bib86","doi-asserted-by":"crossref","unstructured":"Onal,  C. D., Wood,  R. J., & Rus,  D. (2011). Towards printable robotics: Origami-inspired planar fabrication of three-dimensional mechanisms. In 2011 IEEE International Conference on Robotics and Automation (pp. 4608\u20134613). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/ICRA.2011.5980139","DOI":"10.1109\/ICRA.2011.5980139"},{"key":"2021051117414369500_bib87","doi-asserted-by":"crossref","unstructured":"Peng,  X. B., Andrychowicz,  M., Zaremba,  W., & Abbeel,  P. (2018). Sim-to-real transfer of robotic control with dynamics randomization. In 2018 IEEE International Conference on Robotics and Automation (ICRA) (pp. 3803\u20133810). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/ICRA.2018.8460528","DOI":"10.1109\/ICRA.2018.8460528"},{"key":"2021051117414369500_bib88","doi-asserted-by":"crossref","unstructured":"Pfeifer,  R., & Bongard,  J. (2006). How the body shapes the way we think: a new view of intelligence. Cambridge, MA: MIT Press.","DOI":"10.7551\/mitpress\/3585.001.0001"},{"key":"2021051117414369500_bib89","doi-asserted-by":"crossref","unstructured":"Pfeifer,  R., Lungarella,  M., & Iida,  F. (2007). Self-organization, embodiment, and biologically inspired robotics. Science, 318(5853), 1088\u20131093. DOI: https:\/\/doi.org\/10.1126\/science.1145803, PMID: 18006736","DOI":"10.1126\/science.1145803"},{"key":"2021051117414369500_bib90","doi-asserted-by":"crossref","unstructured":"Pfeifer,  R., Lungarella,  M., & Iida,  F. (2012). The challenges ahead for bio-inspired \u2018soft\u2019 robotics. Communications of the ACM, 55(11), 76\u201387. DOI: https:\/\/doi.org\/10.1145\/2366316.2366335","DOI":"10.1145\/2366316.2366335"},{"key":"2021051117414369500_bib91","doi-asserted-by":"crossref","unstructured":"Polygerinos,  P., Correll,  N., Morin,  S. A., Mosadegh,  B., Onal,  C. D., Petersen,  K., Cianchetti,  M., Tolley,  M. T., & Shepherd,  R. F. (2017). Soft robotics: Review of fluid-driven intrinsically soft devices; manufacturing, sensing, control, and applications in human-robot interaction. Advanced Engineering Materials, 19(12), 1700016. DOI: https:\/\/doi.org\/10.1002\/adem.201700016","DOI":"10.1002\/adem.201700016"},{"key":"2021051117414369500_bib92","doi-asserted-by":"crossref","unstructured":"Pozzi,  M., Miguel,  E., Deimel,  R., Malvezzi,  M., Bickel,  B., Brock,  O., & Prattichizzo,  D. (2018). Efficient FEM-based simulation of soft robots modeled as kinematic chains. In 2018 IEEE International Conference on Robotics and Automation (ICRA) (pp. 1\u20138). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/ICRA.2018.8461106","DOI":"10.1109\/ICRA.2018.8461106"},{"key":"2021051117414369500_bib93","doi-asserted-by":"crossref","unstructured":"Pugh,  J. K., Soros,  L. B., & Stanley,  K. O. (2016). Quality diversity: A new frontier for evolutionary computation. Frontiers in Robotics and AI, 3, 40. DOI: https:\/\/doi.org\/10.3389\/frobt.2016.00040","DOI":"10.3389\/frobt.2016.00040"},{"key":"2021051117414369500_bib94","doi-asserted-by":"crossref","unstructured":"Richards,  D., & Amos,  M. (2014). Evolving morphologies with CPPN-NEAT and a dynamic substrate. In ALIFE 2014: The Fourteenth International Conference on the Synthesis and Simulation of Living Systems (pp. 255\u2013262). Cambridge, MA: MIT Press. DOI: https:\/\/doi.org\/10.7551\/978-0-262-32621-6-ch042","DOI":"10.7551\/978-0-262-32621-6-ch042"},{"key":"2021051117414369500_bib95","doi-asserted-by":"crossref","unstructured":"Rieffel,  J., Knox,  D., Smith,  S., & Trimmer,  B. (2014). Growing and evolving soft robots. Artificial Life, 20(1), 143\u2013162. DOI: https:\/\/doi.org\/10.1162\/ARTL_a_00101, PMID: 23373976","DOI":"10.1162\/ARTL_a_00101"},{"key":"2021051117414369500_bib96","doi-asserted-by":"crossref","unstructured":"Rieffel,  J., & Mouret,  J.-B. (2018). Adaptive and resilient soft tensegrity robots. Soft Robotics, 5(3), 318\u2013329. DOI: https:\/\/doi.org\/10.1089\/soro.2017.0066, PMID: 29664708, PMCID: PMC6001847","DOI":"10.1089\/soro.2017.0066"},{"key":"2021051117414369500_bib97","unstructured":"Rieffel,  J., & Pollack,  J. (2005). Crossing the fabrication gap: Evolving assembly plans to build 3D objects. In 2005 IEEE Congress on Evolutionary Computation, volume 1 (pp. 529\u2013536). New York: IEEE."},{"key":"2021051117414369500_bib98","doi-asserted-by":"crossref","unstructured":"Romanishin,  J. W., Gilpin,  K., & Rus,  D. (2013). M-blocks: Momentum-driven, magnetic modular robots. In 2013 IEEE\/RSJ International Conference on Intelligent Robots and Systems (pp. 4288\u20134295). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/IROS.2013.6696971","DOI":"10.1109\/IROS.2013.6696971"},{"key":"2021051117414369500_bib99","doi-asserted-by":"crossref","unstructured":"Romano,  D., Donati,  E., Benelli,  G., & Stefanini,  C. (2019). A review on animal\u2013robot interaction: From bio-hybrid organisms to mixed societies. Biological Cybernetics, 113(3), 201\u2013225. DOI: https:\/\/doi.org\/10.1007\/s00422-018-0787-5, PMID: 30430234","DOI":"10.1007\/s00422-018-0787-5"},{"key":"2021051117414369500_bib100","doi-asserted-by":"crossref","unstructured":"Rosendo,  A., von Atzigen,  M., & Iida,  F. (2017). The trade-off between morphology and control in the co-optimized design of robots. PLOS ONE, 12, e0186107. DOI: https:\/\/doi.org\/10.1371\/journal.pone.0186107, PMID: 29023482, PMCID: PMC5638323","DOI":"10.1371\/journal.pone.0186107"},{"key":"2021051117414369500_bib101","doi-asserted-by":"crossref","unstructured":"Rosser,  K., Kok,  J., Chahl,  J., & Bongard,  J. (2020). Sim2real gap is non-monotonic with robot complexity for morphology-in-the-loop flapping wing design. In 2020 IEEE International Conference on Robotics and Automation (ICRA) (pp. 7001\u20137007). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/ICRA40945.2020.9196539","DOI":"10.1109\/ICRA40945.2020.9196539"},{"key":"2021051117414369500_bib102","unstructured":"Rubanova,  Y., Chen,  R. T. Q., & Duvenaud,  D. K. (2019). Latent ordinary differential equations for irregularly-sampled time series. In H.Wallach, H.Larochelle, A.Beygelzimer, F.d'Alch\u00e9 Buc, E.Fox, & R.Garnett (Eds.), Advances in Neural Information Processing Systems 32 (pp. 5320\u20135330). Red Hook, NY: Curran Associates Inc."},{"key":"2021051117414369500_bib103","doi-asserted-by":"crossref","unstructured":"Rubenstein,  M., Cornejo,  A., & Nagpal,  R. (2014). Programmable self-assembly in a thousand-robot swarm. Science, 345(6198), 795\u2013799. DOI: https:\/\/doi.org\/10.1126\/science.1254295, PMID: 25124435","DOI":"10.1126\/science.1254295"},{"key":"2021051117414369500_bib104","doi-asserted-by":"crossref","unstructured":"Rudy,  S. H., Brunton,  S. L., Proctor,  J. L., & Kutz,  J. N. (2017). Data-driven discovery of partial differential equations. Science Advances, 3(4), e1602614. DOI: https:\/\/doi.org\/10.1126\/sciadv.1602614, PMID: 28508044, PMCID: PMC5406137","DOI":"10.1126\/sciadv.1602614"},{"key":"2021051117414369500_bib105","doi-asserted-by":"crossref","unstructured":"Runge,  G., Wiese,  M., G\u00fcnther,  L., & Raatz,  A. (2017). A framework for the kinematic modeling of soft material robots combining finite element analysis and piecewise constant curvature kinematics. In 2017 3rd International Conference on Control, Automation and Robotics (ICCAR) (pp. 7\u201314). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/ICCAR.2017.7942652","DOI":"10.1109\/ICCAR.2017.7942652"},{"key":"2021051117414369500_bib106","doi-asserted-by":"crossref","unstructured":"Rus,  D., & Tolley,  M. T. (2015). Design, fabrication and control of soft robots. Nature, 521(7553), 467\u2013475. DOI: https:\/\/doi.org\/10.1038\/nature14543, PMID: 26017446","DOI":"10.1038\/nature14543"},{"key":"2021051117414369500_bib107","doi-asserted-by":"crossref","unstructured":"Rus,  D., & Tolley,  M. T. (2018). Design, fabrication and control of origami robots. Nature Reviews Materials, 3(6), 101. DOI: https:\/\/doi.org\/10.1038\/s41578-018-0009-8","DOI":"10.1038\/s41578-018-0009-8"},{"key":"2021051117414369500_bib108","doi-asserted-by":"crossref","unstructured":"Saar,  K. A., Giardina,  F., & Iida,  F. (2018). Model-free design optimization of a hopping robot and its comparison with a human designer. IEEE Robotics and Automation Letters, 3(2), 1245\u20131251. DOI: https:\/\/doi.org\/10.1109\/LRA.2018.2795646","DOI":"10.1109\/LRA.2018.2795646"},{"key":"2021051117414369500_bib109","doi-asserted-by":"crossref","unstructured":"Santina,  C. D., & Rus,  D. (2020). Control oriented modeling of soft robots: The polynomial curvature case. IEEE Robotics and Automation Letters, 5(2), 290\u2013298. DOI: https:\/\/doi.org\/10.1109\/LRA.2019.2955936","DOI":"10.1109\/LRA.2019.2955936"},{"key":"2021051117414369500_bib110","doi-asserted-by":"crossref","unstructured":"Schmid,  P. J.\n           (2010). Dynamic mode decomposition of numerical and experimental data. Journal of Fluid Mechanics, 656, 5\u201328. DOI: https:\/\/doi.org\/10.1017\/S0022112010001217","DOI":"10.1017\/S0022112010001217"},{"key":"2021051117414369500_bib111","doi-asserted-by":"crossref","unstructured":"Schmidt,  M., & Lipson,  H. (2009). Distilling free-form natural laws from experimental data. Science, 324(5923), 81\u201385. DOI: https:\/\/doi.org\/10.1126\/science.1165893, PMID: 19342586","DOI":"10.1126\/science.1165893"},{"key":"2021051117414369500_bib112","doi-asserted-by":"crossref","unstructured":"Schmitt,  F., Piccin,  O., Barb\u00e9,  L., & Bayle,  B. (2018). Soft robots manufacturing: A review. Frontiers in Robotics and AI, 5, 84. DOI: https:\/\/doi.org\/10.3389\/frobt.2018.00084","DOI":"10.3389\/frobt.2018.00084"},{"key":"2021051117414369500_bib113","doi-asserted-by":"crossref","unstructured":"Schulz,  A., Sung,  C., Spielberg,  A., Zhao,  W., Cheng,  R., Grinspun,  E., Rus,  D., & Matusik,  W. (2017). Interactive robogami: An end-to-end system for design of robots with ground locomotion. The International Journal of Robotics Research, 36(10), 1131\u20131147. DOI: https:\/\/doi.org\/10.1177\/0278364917723465","DOI":"10.1177\/0278364917723465"},{"key":"2021051117414369500_bib114","doi-asserted-by":"crossref","unstructured":"Scimeca,  L., Hughes,  J., Maiolino,  P., & Iida,  F. (2019). Model-free soft-structure reconstruction for proprioception using tactile arrays. IEEE Robotics and Automation Letters, 4(3), 2479\u20132484. DOI: https:\/\/doi.org\/10.1109\/LRA.2019.2906548","DOI":"10.1109\/LRA.2019.2906548"},{"key":"2021051117414369500_bib115","doi-asserted-by":"crossref","unstructured":"Shih,  B., Shah,  D., Li,  J., Thuruthel,  T. G., Park,  Y.-L., Iida,  F., Bao,  Z., Kramer-Bottiglio,  R., & Tolley,  M. T. (2020). Electronic skins and machine learning for intelligent soft robots. Science Robotics, 5(41), eaaz9239. DOI: https:\/\/doi.org\/10.1126\/scirobotics.aaz9239, PMID: 33022628","DOI":"10.1126\/scirobotics.aaz9239"},{"key":"2021051117414369500_bib116","doi-asserted-by":"crossref","unstructured":"Silva,  D. F., & Maciel,  A. (2012). A comparative study of physics engines for modeling soft tissue deformation. In 2012 XXXVIII Conferencia Latinoamericana En Informatica (CLEI) (pp. 1\u20137). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/CLEI.2012.6427120","DOI":"10.1109\/CLEI.2012.6427120"},{"key":"2021051117414369500_bib117","doi-asserted-by":"crossref","unstructured":"Sims,  K.\n           (1994). Evolving 3D morphology and behavior by competition. Artificial Life, 1(4), 353\u2013372. DOI: https:\/\/doi.org\/10.1162\/artl.1994.1.4.353","DOI":"10.1162\/artl.1994.1.4.353"},{"key":"2021051117414369500_bib118","unstructured":"Snoek,  J., Larochelle,  H., & Adams,  R. P. (2012). Practical Bayesian optimization of machine learning algorithms. In Proceedings of the 25th International Conference on Neural Information Processing Systems\u2014Volume 2 (pp. 2951\u20132959). Red Hook, NY: Curran Associates Inc."},{"key":"2021051117414369500_bib119","unstructured":"Sun,  Y., Song,  Y. S., & Paik,  J. (2013). Characterization of silicone rubber based soft pneumatic actuators. In 2013 IEEE\/RSJ International Conference on Intelligent Robots and Systems (pp. 4446\u20134453). New York: IEEE."},{"key":"2021051117414369500_bib120","unstructured":"Suthakorn,  J., Cushing,  A. B., & Chirikjian,  G. S. (2003). An autonomous self-replicating robotic system. In Proceedings 2003 IEEE\/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2003) (pp. 137\u2013142). New York: IEEE."},{"key":"2021051117414369500_bib121","doi-asserted-by":"crossref","unstructured":"Tarapore,  D., & Mouret,  J.-B. (2015). Evolvability signatures of generative encodings: Beyond standard performance benchmarks. Information Sciences, 313, 43\u201361. DOI: https:\/\/doi.org\/10.1016\/j.ins.2015.03.046","DOI":"10.1016\/j.ins.2015.03.046"},{"key":"2021051117414369500_bib122","doi-asserted-by":"crossref","unstructured":"Trianni,  V., & L\u00f3pez-Ib\u00e1\u00f1ez,  M. (2015). Advantages of task-specific multi-objective optimisation in evolutionary robotics. PLOS ONE, 10(8), e0136406. DOI: https:\/\/doi.org\/10.1371\/journal.pone.0136406, PMID: 26295151, PMCID: PMC4546428","DOI":"10.1371\/journal.pone.0136406"},{"key":"2021051117414369500_bib123","doi-asserted-by":"crossref","unstructured":"Veenstra,  F., J\u00f8rgensen,  J., & Risi,  S. (2018). Evolution of fin undulation on a physical knifefish-inspired soft robot. In Proceedings of the Genetic and Evolutionary Computation Conference (pp. 157\u2013164). New York: ACM. DOI: https:\/\/doi.org\/10.1145\/3205455.3205583","DOI":"10.1145\/3205455.3205583"},{"key":"2021051117414369500_bib124","doi-asserted-by":"crossref","unstructured":"Vergara,  A., Lau,  Y.-S., Mendoza-Garcia,  R.-F., & Zagal,  J. C. (2017). Soft modular robotic cubes: Toward replicating morphogenetic movements of the embryo. PLOS ONE, 12(1), e0169179. DOI: https:\/\/doi.org\/10.1371\/journal.pone.0169179, PMID: 28060878, PMCID: PMC5218564","DOI":"10.1371\/journal.pone.0169179"},{"key":"2021051117414369500_bib125","doi-asserted-by":"crossref","unstructured":"von Mammen,  S., & Jacob,  C. (2007). Genetic swarm grammar programming: Ecological breeding like a gardener. In 2007 IEEE Congress on Evolutionary Computation (pp. 851\u2013858). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/CEC.2007.4424559","DOI":"10.1109\/CEC.2007.4424559"},{"key":"2021051117414369500_bib126","doi-asserted-by":"crossref","unstructured":"Vujovic,  V., Rosendo,  A., Brodbeck,  L., & Iida,  F. (2017). Evolutionary developmental robotics: Improving morphology and control of physical robots. Artificial Life, 23(2), 169\u2013185. DOI: https:\/\/doi.org\/10.1162\/ARTL_a_00228, PMID: 28513207","DOI":"10.1162\/ARTL_a_00228"},{"key":"2021051117414369500_bib127","doi-asserted-by":"crossref","unstructured":"Wallin,  T., Pikul,  J., & Shepherd,  R. (2018). 3D printing of soft robotic systems. Nature Reviews Materials, 3(6), 84\u2013100. DOI: https:\/\/doi.org\/10.1038\/s41578-018-0002-2","DOI":"10.1038\/s41578-018-0002-2"},{"key":"2021051117414369500_bib128","doi-asserted-by":"crossref","unstructured":"Webster,  R. J.III, & Jones,  B. A. (2010). Design and kinematic modeling of constant curvature continuum robots: A review. The International Journal of Robotics Research, 29(13), 1661\u20131683. DOI: https:\/\/doi.org\/10.1177\/0278364910368147","DOI":"10.1177\/0278364910368147"},{"key":"2021051117414369500_bib129","doi-asserted-by":"crossref","unstructured":"Wehner,  M., Truby,  R. L., Fitzgerald,  D. J., Mosadegh,  B., Whitesides,  G. M., Lewis,  J. A., & Wood,  R. J. (2016). An integrated design and fabrication strategy for entirely soft, autonomous robots. Nature, 536(7617), 451\u2013455. DOI: https:\/\/doi.org\/10.1038\/nature19100, PMID: 27558065","DOI":"10.1038\/nature19100"},{"key":"2021051117414369500_bib130","doi-asserted-by":"crossref","unstructured":"Werfel,  J., Petersen,  K., & Nagpal,  R. (2014). Designing collective behavior in a termite-inspired robot construction team. Science, 343(6172), 754\u2013758. DOI: https:\/\/doi.org\/10.1126\/science.1245842, PMID: 24531967","DOI":"10.1126\/science.1245842"},{"key":"2021051117414369500_bib131","doi-asserted-by":"crossref","unstructured":"Whitesides,  G. M.\n           (2018). Soft robotics. Angewandte Chemie International Edition, 57(16), 4258\u20134273. DOI: https:\/\/doi.org\/10.1002\/anie.201800907, PMID: 29517838","DOI":"10.1002\/anie.201800907"},{"key":"2021051117414369500_bib132","doi-asserted-by":"crossref","unstructured":"Yarbasi,  E. Y., & Samur,  E. (2018). Design and evaluation of a continuum robot with extendable balloons. Mechanical Sciences, 9(1), 51\u201360. DOI: https:\/\/doi.org\/10.5194\/ms-9-51-2018","DOI":"10.5194\/ms-9-51-2018"},{"key":"2021051117414369500_bib133","doi-asserted-by":"crossref","unstructured":"Zappetti,  D., Mintchev,  S., Shintake,  J., & Floreano,  D. (2017). Bio-inspired tensegrity soft modular robots. In M.Mangan, M.Cutkosky, A.Mura, P. F.Verschure, T.Prescott, & N.Lepora (Eds.), Biomimetic and biohybrid systems (pp. 497\u2013508). Cham: Springer. DOI: https:\/\/doi.org\/10.1007\/978-3-319-63537-8_42","DOI":"10.1007\/978-3-319-63537-8_42"},{"key":"2021051117414369500_bib134","doi-asserted-by":"crossref","unstructured":"Zhakypov,  Z., & Paik,  J. (2018). Design methodology for constructing multimaterial origami robots and machines. IEEE Transactions on Robotics, 34(1), 151\u2013165. DOI: https:\/\/doi.org\/10.1109\/TRO.2017.2775655","DOI":"10.1109\/TRO.2017.2775655"},{"key":"2021051117414369500_bib135","doi-asserted-by":"crossref","unstructured":"Zhang,  J., Zhou,  M., Huang,  Y., Ren,  P., Wu,  Z., Wang,  X., & Zhao,  S. F. (2017). A smoothed finite element-based elasticity model for soft bodies. Mathematical Problems in Engineering, 2017, 467356. DOI: https:\/\/doi.org\/10.1155\/2017\/1467356","DOI":"10.1155\/2017\/1467356"},{"key":"2021051117414369500_bib136","doi-asserted-by":"crossref","unstructured":"Zhang,  Z., Dequidt,  J., Kruszewski,  A., Largilliere,  F., & Duriez,  C. (2016). Kinematic modeling and observer based control of soft robot using real-time finite element method. In 2016 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 5509\u20135514). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/IROS.2016.7759810","DOI":"10.1109\/IROS.2016.7759810"},{"key":"2021051117414369500_bib137","doi-asserted-by":"crossref","unstructured":"Zheng,  G., Goury,  O., Thieffry,  M., Kruszewski,  A., & Duriez,  C. (2019). Controllability pre-verification of silicone soft robots based on finite-element method. In 2019 International Conference on Robotics and Automation (ICRA) (pp. 7395\u20137400). New York: IEEE. DOI: https:\/\/doi.org\/10.1109\/ICRA.2019.8794370","DOI":"10.1109\/ICRA.2019.8794370"}],"container-title":["Artificial Life"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/direct.mit.edu\/artl\/article-pdf\/26\/4\/484\/1916006\/artl_a_00330.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"http:\/\/direct.mit.edu\/artl\/article-pdf\/26\/4\/484\/1916006\/artl_a_00330.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,11]],"date-time":"2021-05-11T17:47:58Z","timestamp":1620755278000},"score":1,"resource":{"primary":{"URL":"https:\/\/direct.mit.edu\/artl\/article\/26\/4\/484\/97301\/Reality-Assisted-Evolution-of-Soft-Robots-through"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":137,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2021,2,1]]},"published-print":{"date-parts":[[2021,2,1]]}},"URL":"https:\/\/doi.org\/10.1162\/artl_a_00330","relation":{},"ISSN":["1064-5462","1530-9185"],"issn-type":[{"value":"1064-5462","type":"print"},{"value":"1530-9185","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2020]]},"published":{"date-parts":[[2020]]}}}