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Energy-saving movement strategies in animals and plants for robot design

Nature Reviews Bioengineering (2025)Cite this article

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Abstract

Unlike living organisms, which evolved to adapt to dynamic conditions, robots often become less agile in complex scenarios, prompting roboticists to reduce environmental complexities to ease robot operations. However, the strategies implemented by animals and plants to achieve energy-saving movements in complex environments can inspire the design of more resilient autonomous robots with lower energy consumption. In nature, movement strategies evolved to balance energy expenditure and resource acquisition to survive in unpredictable environments. This is particularly relevant for robots operating over large distances or in resource-limited conditions. In this Review, we present a performance analysis of movement strategies in both natural and artificial systems and across different environments — terrain, soil, underwater and air — and emphasize how energy-saving design principles can be used to widen the operativity of robots. We discuss the importance of the cost of transport as a metric for assessing movement economy and propose its use, not only for animals, but also to benchmark movement by growth and seed dispersal in plants. Despite the profound differences in energy harvesting strategies, as plants produce organic matter using energy from light and animals obtain energy by consuming organic matter, studying both can lead to energy-saving designs in bioinspired robots.

Key points

  • Movement strategies in natural and artificial systems are compared across terrain, soil, underwater and air to identify design principles that economize energy and extend robot operativity.

  • Cost of transport is used to measure the ‘economy’ of movements in robots, animals and, for the first time, in plants to enable a fundamental, function-related, energy-based comparison between specific species and their artificial counterparts.

  • Mechanical intelligence and environmental energy harvesting are the key enablers of energy-saving movements in biological systems.

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Fig. 1: Schematic to inform design of long-lasting robotic systems.
Fig. 2: Examples of biological models, energy-saving mechanisms and bioinspired robots.
Fig. 3: Benchmarking of natural and artificial systems.

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References

  1. Rivero-Moreno, Y. et al. Robotic surgery: a comprehensive review of the literature and current trends. Cureus 15, e42370 (2023).

    Google Scholar 

  2. Bernardo, R., Sousa, J. M. C. & Gonçalves, P. J. S. Survey on robotic systems for internal logistics. J. Manuf. Syst. 65, 339–350 (2022).

    Article  Google Scholar 

  3. Oliveira, L. F. P., Moreira, A. P. & Silva, M. F. Advances in agriculture robotics: a state-of-the-art review and challenges ahead. Robotics 10, 52 (2021).

    Article  Google Scholar 

  4. Sanneman, L., Fourie, C. & Shah, J. A. The state of industrial robotics: emerging technologies, challenges, and key research directions. Found. Trends Robot. 8, 225–306 (2021).

    Article  Google Scholar 

  5. Melenbrink, N., Werfel, J. & Menges, A. On-site autonomous construction robots: towards unsupervised building. Autom. Constr. 119, 103312 (2020).

    Article  Google Scholar 

  6. Lee, A. J. et al. Survey of robotics technologies for civil infrastructure inspection. J. Infrastruct. Intell. Resil. 2, 100018 (2023).

    Google Scholar 

  7. Chien, S. A., Visentin, G. & Basich, C. Exploring beyond earth using space robotics. Sci. Robot. 9, eadi6424 (2024).

    Article  Google Scholar 

  8. Li, D. et al. A survey of space robotic technologies for on-orbit assembly. Space Sci. Technol. 2022, 9849170 (2022).

    Article  Google Scholar 

  9. Laschi, C. & Mazzolai, B. Lessons from animals and plants: the symbiosis of morphological computation and soft robotics. IEEE Robot. Autom. Mag. 23, 107–114 (2016).

    Article  Google Scholar 

  10. Rowe, N. & Speck, T. Plant growth forms: an ecological and evolutionary perspective. New Phytol. 166, 61–72 (2005).

    Article  Google Scholar 

  11. Minetti, A. E. & Alexander, R. M. A theory of metabolic costs for bipedal gaits. J. Theor. Biol. 186, 467–476 (1997).

    Article  Google Scholar 

  12. Mochon, S. & McMahon, T. A. Ballistic walking. J. Biomech. 13, 49–57 (1980).

    Article  Google Scholar 

  13. Reher, J., Cousineau, E. A., Hereid, A., Hubicki, C. M. & Ames, A. D. Realizing dynamic and efficient bipedal locomotion on the humanoid robot DURUS. In Proc. 2016 IEEE International Conference on Robotics and Automation (ICRA) 1794–1801 (IEEE, 2016).

  14. Collins, S. H. & Ruina, A. A bipedal walking robot with efficient and human-like gait. In Proc. 2005 IEEE International Conference on Robotics and Automation 1983–1988 (IEEE, 2005).

  15. Tsagarakis, N. G. et al. WALK‐MAN: a high‐performance humanoid platform for realistic environments. J. Field Robot. 34, 1225–1259 (2017).

    Article  Google Scholar 

  16. Kashiri, N. et al. An overview on principles for energy efficient robot locomotion. Front. Robot. AI 5, 129 (2018).

    Article  Google Scholar 

  17. Makedon, V., Mykhailenko, O. & Vazov, R. Dominants and features of growth of the world market of robotics. Eur. J. Manag. Issues 29, 133–141 (2021).

    Article  Google Scholar 

  18. Salguero-Gómez, R. et al. Fast–slow continuum and reproductive strategies structure plant life-history variation worldwide. Proc. Natl Acad. Sci. USA 113, 230–235 (2016).

    Article  Google Scholar 

  19. Oli, M. K. The fast–slow continuum and mammalian life-history patterns: an empirical evaluation. Basic Appl. Ecol. 5, 449–463 (2004).

    Article  Google Scholar 

  20. Lailvaux, S. P. & Husak, J. F. Predicting life-history trade-offs with whole-organism performance. Integr. Comp. Biol. 57, 325–332 (2017).

    Article  Google Scholar 

  21. Alexander, R. M. Tyrannosaurus on the run. Nature 379, 121 (1996).

    Article  Google Scholar 

  22. Mazzolai, B., Tramacere, F., Fiorello, I. & Margheri, L. The bio-engineering approach for plant investigations and growing robots. A mini-review. Front. Robot. AI 7, 573014 (2020).

    Article  Google Scholar 

  23. Brackenbury, J. Caterpillar kinematics. Nature 390, 453 (1997).

    Article  Google Scholar 

  24. Lin, H.-T., Leisk, G. G. & Trimmer, B. GoQBot: a caterpillar-inspired soft-bodied rolling robot. Bioinspir. Biomim. 6, 026007 (2011).

    Article  Google Scholar 

  25. Radhakrishnan, V. Locomotion: dealing with friction. Proc. Natl Acad. Sci. USA 95, 5448–5455 (1998).

    Article  Google Scholar 

  26. Casey, T. M. Energetics of caterpillar locomotion: biomechanical constraints of a hydraulic skeleton. Science 252, 112–114 (1991).

    Article  Google Scholar 

  27. Full, R. J., Zuccarello, D. A. & Tullis, A. Effect of variation in form on the cost of terrestrial locomotion. J. Exp. Biol. 150, 233–246 (1990).

    Article  Google Scholar 

  28. Lin, H.-T. & Trimmer, B. Caterpillars use the substrate as their external skeleton: a behavior confirmation. Commun. Integr. Biol. 3, 471–474 (2010).

    Article  Google Scholar 

  29. Vaughan, S. C., Lin, H. & Trimmer, B. A. Caterpillar climbing: robust, tension-based omni-directional locomotion. J. Insect Sci. 18, 13 (2018).

    Article  Google Scholar 

  30. Ariizumi, R. & Matsuno, F. Dynamical analysis of sidewinding locomotion by a snake-like robot. In Proc. 2013 IEEE International Conference on Robotics and Automation 5149–5154 (IEEE, 2013).

  31. Fu, Q., Astley, H. C. & Li, C. Snakes combine vertical and lateral bending to traverse uneven terrain. Bioinspir. Biomim. 17, 036009 (2022).

    Article  Google Scholar 

  32. Ariizumi, R. & Matsuno, F. Dynamic analysis of three snake robot gaits. IEEE Trans. Robot. 33, 1075–1087 (2017).

    Article  Google Scholar 

  33. McMahon, T. A. Mechanics of locomotion. Int. J. Robot. Res. 3, 4–28 (1984).

    Article  Google Scholar 

  34. McGeer, T. Passive dynamic walking. Int. J. Robot. Res. 9, 62–82 (1990).

    Article  Google Scholar 

  35. Tucker, V. A. The energetic cost of moving about. Am. Sci. 63, 413–419 (1975).

    Google Scholar 

  36. Collins, S. H., Wisse, M. & Ruina, A. A three-dimensional passive-dynamic walking robot with two legs and knees. Int. J. Robot. Res. 20, 607–615 (2001).

    Article  Google Scholar 

  37. Collins, S. H., Adamczyk, P. G. & Kuo, A. D. Dynamic arm swinging in human walking. Proc. R. Soc. B 276, 3679–3688 (2009).

    Article  Google Scholar 

  38. Tedrake, R., Zhang, T. W. & Seung, H. S. Stochastic policy gradient reinforcement learning on a simple 3D biped. In Proc. 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566) 2849–2854 (IEEE, 2004).

  39. Collins, S., Ruina, A., Tedrake, R. & Wisse, M. Efficient bipedal robots based on passive-dynamic walkers. Science 307, 1082–1085 (2005).

    Article  Google Scholar 

  40. Müller, V. C. & Hoffmann, M. What is morphological computation? On how the body contributes to cognition and control. Artif. Life 23, 1–24 (2017).

    Article  Google Scholar 

  41. Rudman, K., Aspden, R. & Meakin, J. Compression or tension? The stress distribution in the proximal femur. Biomed. Eng. Online 5, 12 (2006).

    Article  Google Scholar 

  42. Seok, S. et al. Design principles for highly efficient quadrupeds and implementation on the MIT Cheetah robot. In Proc. 2013 IEEE International Conference on Robotics and Automation 3307–3312 (IEEE, 2013).

  43. Ananthanarayanan, A., Azadi, M. & Kim, S. Towards a bio-inspired leg design for high-speed running. Bioinspir. Biomim. 7, 046005 (2012).

    Article  Google Scholar 

  44. Badri-Spröwitz, A., Aghamaleki Sarvestani, A., Sitti, M. & Daley, M. A. BirdBot achieves energy-efficient gait with minimal control using avian-inspired leg clutching. Sci. Robot. 7, eabg4055 (2022).

    Article  Google Scholar 

  45. Blickhan, R. et al. Intelligence by mechanics. Philos. Trans. R. Soc. A 365, 199–220 (2007).

    Article  MathSciNet  Google Scholar 

  46. Ilton, M. et al. The principles of cascading power limits in small, fast biological and engineered systems. Science 360, eaao1082 (2018).

    Article  Google Scholar 

  47. Bonsignori, G. et al. The green leafhopper, Cicadella viridis (Hemiptera, Auchenorrhyncha, Cicadellidae), jumps with near-constant acceleration. J. Exp. Biol. 216, 1270–1279 (2013).

    Article  Google Scholar 

  48. Ker, R. F., Alexander, R. M. & Bennett, M. B. Why are mammalian tendons so thick? J. Zool. 216, 309–324 (1988).

    Article  Google Scholar 

  49. Ker, R. F. Dynamic tensile properties of the plantaris tendon of sheep (Ovis aries). J. Exp. Biol. 93, 283–302 (1981).

    Article  Google Scholar 

  50. Vincent, J. F. V. & Wegst, U. G. K. Design and mechanical properties of insect cuticle. Arthropod Struct. Dev. 33, 187–199 (2004).

    Article  Google Scholar 

  51. Vogler, H. et al. The pollen tube: a soft shell with a hard core. Plant. J. 73, 617–627 (2013).

    Article  Google Scholar 

  52. Nezhad, A. S., Naghavi, M., Packirisamy, M., Bhat, R. & Geitmann, A. Quantification of the Young’s modulus of the primary plant cell wall using bending-lab-on-chip (BLOC). Lab Chip 13, 2599–2608 (2013).

    Article  Google Scholar 

  53. Li, F. et al. Jumping like an insect: design and dynamic optimization of a jumping mini robot based on bio-mimetic inspiration. Mechatronics 22, 167–176 (2012).

    Article  Google Scholar 

  54. Soffiatti, P., Fort, E., Heinz, C. & Rowe, N. P. Trellis-forming stems of a tropical liana Condylocarpon guianense (Apocynaceae): a plant-made safety net constructed by simple “start-stop” development. Front. Plant Sci. 13, 1016195 (2022).

    Article  Google Scholar 

  55. Hattermann, T., Petit-Bagnard, L., Heinz, C., Heuret, P. & Rowe, N. P. Mind the gap: reach and mechanical diversity of searcher shoots in climbing plants. Front. For. Glob. Change 5, 836247 (2022).

    Article  Google Scholar 

  56. Naselli, G. A. et al. A soft continuum robotic arm with a climbing plant‐inspired adaptive behavior for minimal sensing, actuation, and control effort. Adv. Intell. Syst. 6, 2300537 (2024).

    Article  Google Scholar 

  57. Del Dottore, E., Mondini, A., Rowe, N. & Mazzolai, B. A growing soft robot with climbing plant–inspired adaptive behaviors for navigation in unstructured environments. Sci. Robot. 9, eadi5908 (2024).

    Article  Google Scholar 

  58. Aguilar-Duque, J. I., Hernández-Arellano, J. L., Avelar-Sosa, L., Amaya-Parra, G. & Tamayo-Pérez, U. J. in Best Practices in Manufacturing Processes (eds García Alcaraz, J. L. et al.) 347–366 (Springer, 2019).

  59. Sadeghi, A., Tonazzini, A., Popova, L. & Mazzolai, B. A novel growing device inspired by plant root soil penetration behaviors. PLoS One 9, e90139 (2014).

    Article  Google Scholar 

  60. Del Dottore, E., Sadeghi, A., Mondini, A., Mattoli, V. & Mazzolai, B. Toward growing robots: a historical evolution from cellular to plant-inspired robotics. Front. Robot. AI 5, 16 (2018).

    Article  Google Scholar 

  61. Del Dottore, E. & Mazzolai, B. Perspectives on computation in plants. Artif. Life 29, 336–350 (2023).

    Article  Google Scholar 

  62. Speck, T. & Rowe, N. P. in The Evolution of Plant Architecture (eds Kurmann, N. H. & Hemsley, A. R.) 447–479 (Kew, 1999).

  63. Maladen, R. D., Umbanhowar, P. B., Ding, Y., Masse, A. & Goldman, D. I. Granular lift forces predict vertical motion of a sand-swimming robot. In Proc. 2011 IEEE International Conference on Robotics and Automation 1398–1403 (IEEE, 2011).

  64. Zhang, W., Huang, R., Xiang, J. & Zhang, N. Recent advances in bio-inspired geotechnics: from burrowing strategy to underground structures. Gondwana Res. 130, 1–17 (2024).

    Article  Google Scholar 

  65. Martinez, A. et al. Bio-inspired geotechnical engineering: principles, current work, opportunities and challenges. Geotechnique 72, 687–705 (2022).

    Article  Google Scholar 

  66. Patino-Ramirez, F. & O’Sullivan, C. Optimal tip shape for minimum drag and lift during horizontal penetration in granular media. Acta Geotech. 19, 19–38 (2024).

    Article  Google Scholar 

  67. Quillin, K. J. Kinematic scaling of locomotion by hydrostatic animals: ontogeny of peristaltic crawling by the earthworm Lumbricus terrestris. J. Exp. Biol. 202, 661–674 (1999).

    Article  Google Scholar 

  68. Ali, O., Cheddadi, I., Landrein, B. & Long, Y. Revisiting the relationship between turgor pressure and plant cell growth. New Phytol. 238, 62–69 (2023).

    Article  Google Scholar 

  69. Ruiz, S., Schymanski, S. J. & Or, D. Mechanics and energetics of soil penetration by earthworms and plant roots: higher rates cost more. Vadose Zone J. 16, 1–16 (2017).

    Article  Google Scholar 

  70. Pirrone, S. R. M., Del Dottore, E., Sibille, L. & Mazzolai, B. A methodology to investigate the design requirements of plant root-inspired robots for soil exploration. IEEE Robot. Autom. Lett. 8, 3438–3445 (2023).

    Article  Google Scholar 

  71. Dorgan, K. M. The biomechanics of burrowing and boring. J. Exp. Biol. 218, 176–183 (2015).

    Article  Google Scholar 

  72. Pirrone, S. R. M., Del Dottore, E., Sibille, L. & Mazzolai, B. Investigations of bioinspired soil penetration strategies via a numerical model: does radial expansion improve soil intruder performances? Acta Geotech. 19, 1275–1293 (2024).

    Article  Google Scholar 

  73. Keudel, M. & Schrader, S. Axial and radial pressure exerted by earthworms of different ecological groups. Biol. Fertil. Soils 29, 262–269 (1999).

    Article  Google Scholar 

  74. Materechera, S. A., Alston, A. M., Kirby, J. M. & Dexter, A. R. Influence of root diameter on the penetration of seminal roots into a compacted subsoil. Plant Soil 144, 297–303 (1992).

    Article  Google Scholar 

  75. Das, R., Babu, S. P. M., Visentin, F., Palagi, S. & Mazzolai, B. An earthworm-like modular soft robot for locomotion in multi-terrain environments. Sci. Rep. 13, 1571 (2023).

    Article  Google Scholar 

  76. Sadeghi, A., Mondini, A. & Mazzolai, B. Toward self-growing soft robots inspired by plant roots and based on additive manufacturing technologies. Soft Robot. 4, 211–223 (2017).

    Article  Google Scholar 

  77. Sadeghi, A., Del Dottore, E., Mondini, A. & Mazzolai, B. Passive morphological adaptation for obstacle avoidance in a self-growing robot produced by additive manufacturing. Soft Robot. 7, 85–94 (2020).

    Article  Google Scholar 

  78. Naclerio, N. D. et al. Controlling subterranean forces enables a fast, steerable, burrowing soft robot. Sci. Robot. 6, eabe2922 (2021).

    Article  Google Scholar 

  79. Del Dottore, E., Mondini, A., Bray, D. & Mazzolai, B. Miniature soil moisture sensors for a root-inspired burrowing growing robot. In Proc. Biomimetic and Biohybrid Systems, 12th International Conference, Living Machines 2023 (eds Meder, F. et al.) 184–196 (Springer, 2023).

  80. Abraham, Y. & Elbaum, R. Hygroscopic movements in Geraniaceae: the structural variations that are responsible for coiling or bending. New Phytol. 199, 584–594 (2013).

    Article  Google Scholar 

  81. Abraham, Y. et al. Tilted cellulose arrangement as a novel mechanism for hygroscopic coiling in the stork’s bill awn. J. R. Soc. Interface 9, 640–647 (2012).

    Article  Google Scholar 

  82. Evangelista, D., Hotton, S. & Dumais, J. The mechanics of explosive dispersal and self-burial in the seeds of the filaree, Erodium cicutarium (Geraniaceae). J. Exp. Biol. 214, 521–529 (2011).

    Article  Google Scholar 

  83. Cecchini, L. et al. 4D printing of humidity‐driven seed inspired soft robots. Adv. Sci. 10, 2205146 (2023).

    Article  Google Scholar 

  84. Luo, D. et al. Autonomous self-burying seed carriers for aerial seeding. Nature 614, 463–470 (2023).

    Article  Google Scholar 

  85. Fiorello, I., Ronzan, M., Speck, T., Sinibaldi, E. & Mazzolai, B. A biohybrid self‐dispersing miniature machine using wild oat fruit awns for reforestation and precision agriculture. Adv. Mater. 36, e2313906 (2024).

    Article  Google Scholar 

  86. Hasan, K. et al. Oceanic challenges to technological solutions: a review of autonomous underwater vehicle path technologies in biomimicry, control, navigation, and sensing. IEEE Access 12, 46202–46231 (2024).

    Article  Google Scholar 

  87. Stoner, A. W., Ryer, C. H., Parker, S. J., Auster, P. J. & Wakefield, W. W. Evaluating the role of fish behavior in surveys conducted with underwater vehicles. Can. J. Fish. Aquat. Sci. 65, 1230–1243 (2008).

    Article  Google Scholar 

  88. Sfakiotakis, M., Lane, D. M. & Davies, J. B. C. Review of fish swimming modes for aquatic locomotion. IEEE J. Ocean. Eng. 24, 237–252 (1999).

    Article  Google Scholar 

  89. Bainbridge, R. The speed of swimming of fish as related to size and to the frequency and amplitude of the tail beat. J. Exp. Biol. 35, 109–133 (1958).

    Article  Google Scholar 

  90. Wang, R., Wang, S., Wang, Y., Cheng, L. & Tan, M. Development and motion control of biomimetic underwater robots: a survey. IEEE Trans. Syst. Man. Cybern. Syst. 52, 833–844 (2022).

    Article  Google Scholar 

  91. Shintake, J., Cacucciolo, V., Shea, H. & Floreano, D. Soft biomimetic fish robot made of dielectric elastomer actuators. Soft Robot. 5, 466–474 (2018).

    Article  Google Scholar 

  92. Di Santo, V. et al. Convergence of undulatory swimming kinematics across a diversity of fishes. Proc. Natl Acad. Sci. USA 118, e2113206118 (2021).

    Article  Google Scholar 

  93. Katzschmann, R. K., DelPreto, J., MacCurdy, R. & Rus, D. Exploration of underwater life with an acoustically controlled soft robotic fish. Sci. Robot. 3, eaar3449 (2018).

    Article  Google Scholar 

  94. Calisti, M. & Laschi, C. Morphological and control criteria for self-stable underwater hopping. Bioinspir. Biomim. 13, 016001 (2017).

    Article  Google Scholar 

  95. Chellapurath, M. et al. Locomotory behaviour of the intertidal marble crab (Pachygrapsus marmoratus) supports the underwater spring-loaded inverted pendulum as a fundamental model for punting in animals. Bioinspir. Biomim. 15, 055004 (2020).

    Article  Google Scholar 

  96. Picardi, G. et al. Bioinspired underwater legged robot for seabed exploration with low environmental disturbance. Sci. Robot. 5, eaaz1012 (2020).

    Article  Google Scholar 

  97. Giorgio-Serchi, F., Arienti, A. & Laschi, C. Underwater soft-bodied pulsed-jet thrusters: actuator modeling and performance profiling. Int. J. Robot. Res. 35, 1308–1329 (2016).

    Article  Google Scholar 

  98. Giorgio Serchi, F., Arienti, A. & Laschi, C. Biomimetic vortex propulsion: toward the new paradigm of soft unmanned underwater vehicles. IEEE/ASME Trans. Mechatron. 18, 484–493 (2013).

    Article  Google Scholar 

  99. Trueman, E. R. & Packard, A. Motor performances of some cephalopods. J. Exp. Biol. 49, 495–507 (1968).

    Article  Google Scholar 

  100. Renda, F., Giorgio Serchi, F., Boyer, F. & Laschi, C. Structural dynamics of a pulsed-jet propulsion system for underwater soft robots. Int. J. Adv. Robot. Syst. https://doi.org/10.5772/60143 (2015).

  101. Renda, F. et al. A unified multi-soft-body dynamic model for underwater soft robots. Int. J. Robot. Res. 37, 648–666 (2018).

    Article  Google Scholar 

  102. Seibel, B. A. & Drazen, J. C. The rate of metabolism in marine animals: environmental constraints, ecological demands and energetic opportunities. Philos. Trans. R. Soc. B 362, 2061–2078 (2007).

    Article  Google Scholar 

  103. Gemmell, B. J. et al. Passive energy recapture in jellyfish contributes to propulsive advantage over other metazoans. Proc. Natl Acad. Sci. USA 110, 17904–17909 (2013).

    Article  Google Scholar 

  104. Villanueva, A., Smith, C. & Priya, S. A biomimetic robotic jellyfish (Robojelly) actuated by shape memory alloy composite actuators. Bioinspir. Biomim. 6, 036004 (2011).

    Article  Google Scholar 

  105. Templin, R. J. The spectrum of animal flight: insects to pterosaurs. Prog. Aerosp. Sci. 36, 393–436 (2000).

    Article  Google Scholar 

  106. Jafferis, N. T., Helbling, E. F., Karpelson, M. & Wood, R. J. Untethered flight of an insect-sized flapping-wing microscale aerial vehicle. Nature 570, 491–495 (2019).

    Article  Google Scholar 

  107. Jafferis, N. T., Graule, M. A. & Wood, R. J. Non-linear resonance modeling and system design improvements for underactuated flapping-wing vehicles. In Proc. 2016 IEEE International Conference on Robotics and Automation (ICRA) 3234–3241 (IEEE, 2016).

  108. Marden, J. H. Maximum lift production during takeoff in flying animals. J. Exp. Biol. 130, 235–258 (1987).

    Article  Google Scholar 

  109. Nachtigall, W., Hanauer-Thieser, U. & Mörz, M. Flight of the honey bee VII: metabolic power versus flight speed relation. J. Comp. Physiol. B 165, 484–489 (1995).

    Article  Google Scholar 

  110. Nachtigall, W. & Hanauer-Thieser, U. Flight of the honeybee: V. Drag and lift coefficients of the bee’s body; implications for flight dynamics. J. Comp. Physiol. B 162, 267–277 (1992).

    Article  Google Scholar 

  111. Kovac, M., Wassim-Hraiz, Fauria, O., Zufferey, J.-C. & Floreano, D. The EPFL jumpglider: a hybrid jumping and gliding robot with rigid or folding wings. In Proc. 2011 IEEE International Conference on Robotics and Biomimetics 1503–1508 (IEEE, 2011).

  112. Lentink, D., Dickson, W. B., Van Leeuwen, J. L. & Dickinson, M. H. Leading-edge vortices elevate lift of autorotating plant seeds. Science 324, 1438–1440 (2009).

    Article  Google Scholar 

  113. Norberg, R. Å. Autorotation, self‐stability, and structure of single‐winged fruits and seeds (Samaras) with comparative remarks on animal flight. Biol. Rev. 48, 561–596 (1973).

    Article  Google Scholar 

  114. Nave, G. K. et al. Wind dispersal of natural and biomimetic maple samaras. Biomimetics 6, 23 (2021).

    Article  Google Scholar 

  115. Holden, J. R., Caley, T. M. & Turner, M. G. Maple seed performance as a wind turbine. In Proc. 53rd AIAA Aerospace Sciences Meeting https://doi.org/10.2514/6.2015-1304 (American Institute of Aeronautics and Astronautics, 2015).

  116. Dai, J., Liu, D., Wen, L. & Long, X. Research on power coefficient of wind turbines based on SCADA data. Renew. Energy 86, 206–215 (2016).

    Article  Google Scholar 

  117. Herrera, C. et al. Structural design and manufacturing process of a low scale bio-inspired wind turbine blades. Compos. Struct. 208, 1–12 (2019).

    Article  Google Scholar 

  118. Ulrich, E. R., Pines, D. J. & Humbert, J. S. From falling to flying: the path to powered flight of a robotic samara nano air vehicle. Bioinspir. Biomim. 5, 045009 (2010).

    Article  Google Scholar 

  119. Cikalleshi, K. et al. A printed luminescent flier inspired by plant seeds for eco-friendly physical sensing. Sci. Adv. 9, eadi8492 (2023).

    Article  Google Scholar 

  120. Pounds, P. & Singh, S. Samara: biologically inspired self-deploying sensor networks. IEEE Potentials 34, 10–14 (2015).

    Article  Google Scholar 

  121. Wiesemüller, F. et al. Transient bio-inspired gliders with embodied humidity responsive actuators for environmental sensing. Front. Robot. AI 9, 1011793 (2022).

    Article  Google Scholar 

  122. Cummins, C. et al. A separated vortex ring underlies the flight of the dandelion. Nature 562, 414–418 (2018).

    Article  Google Scholar 

  123. Ledda, P. G., Siconolfi, L., Viola, F., Camarri, S. & Gallaire, F. Flow dynamics of a dandelion pappus: a linear stability approach. Phys. Rev. Fluids 4, 071901 (2019).

    Article  Google Scholar 

  124. Chen, Y. et al. Light-driven dandelion-inspired microfliers. Nat. Commun. 14, 3036 (2023).

    Article  Google Scholar 

  125. Mariani, S. et al. A biodegradable, porous flier inspired by a parachute‐like Tragopogon fruit for environmental preservation. Small 21, 2403582 (2025).

    Article  Google Scholar 

  126. Donelan, J. M., Kram, R. & Kuo, A. D. Mechanical work for step-to-step transitions is a major determinant of the metabolic cost of human walking. J. Exp. Biol. 205, 3717–3727 (2002).

    Article  Google Scholar 

  127. Hae-Won, P., Wensing, P. M. & Kim, S. Online planning for autonomous running jumps over obstacles in high-speed quadrupeds. In Proc. 2015 Robotics: Science and Systems Conference (RSS) (eds Buchli, J. et al.) 1–9 (MIT Press, 2015).

  128. Kim, K., Spieler, P., Lupu, E.-S., Ramezani, A. & Chung, S.-J. A bipedal walking robot that can fly, slackline, and skateboard. Sci. Robot. 6, eabf8136 (2021).

    Article  Google Scholar 

  129. Ohlberger, J., Staaks, G. & Hölker, F. Swimming efficiency and the influence of morphology on swimming costs in fishes. J. Comp. Physiol. B 176, 17–25 (2006).

    Article  Google Scholar 

  130. Aleyev, Y. G. in Nekton 367–370 (Springer, 1977).

  131. Schmidt-Nielsen, K. Locomotion: energy cost of swimming, flying, and running. Science 177, 222–228 (1972).

    Article  Google Scholar 

  132. Kraskura, K. et al. Sex-specific differences in swimming, aerobic metabolism and recovery from exercise in adult coho salmon (Oncorhynchus kisutch) across ecologically relevant temperatures. Conserv. Physiol. 9, coab016 (2021).

    Article  Google Scholar 

  133. Nelson, J., Tang, Y. & Boutilier, R. The effects of salinity change on the exercise performance of two Atlantic cod (Gadus morhua) populations inhabiting different environments. J. Exp. Biol. 199, 1295–1309 (1996).

    Article  Google Scholar 

  134. Seebacher, F., Webster, M. M., James, R. S., Tallis, J. & Ward, A. J. W. Morphological differences between habitats are associated with physiological and behavioural trade-offs in stickleback (Gasterosteus aculeatus). R. Soc. Open Sci. 3, 160316 (2016).

    Article  Google Scholar 

  135. Oldham, T., Nowak, B., Hvas, M. & Oppedal, F. Metabolic and functional impacts of hypoxia vary with size in Atlantic salmon. Comp. Biochem. Physiol. A 231, 30–38 (2019).

    Article  Google Scholar 

  136. Jahn, M. & Seebacher, F. Variations in cost of transport and their ecological consequences: a review. J. Exp. Biol. 225, jeb243646 (2022).

    Article  Google Scholar 

  137. Wilson, R. S., Husak, J. F., Halsey, L. G. & Clemente, C. J. Predicting the movement speeds of animals in natural environments. Integr. Comp. Biol. 55, 1125–1141 (2015).

    Article  Google Scholar 

  138. Han, A. X., Berlin, C. & Ellerby, D. J. Field swimming behavior in largemouth bass deviates from predictions based on economy and propulsive efficiency. J. Exp. Biol. 220, 3204–3208 (2017).

    Article  Google Scholar 

  139. Burden, S. A., Libby, T., Jayaram, K., Sponberg, S. & Donelan, J. M. Why animals can outrun robots. Sci. Robot. 9, eadi9754 (2024).

    Article  Google Scholar 

  140. Huang, X. et al. Chasing biomimetic locomotion speeds: creating untethered soft robots with shape memory alloy actuators. Sci. Robot. 3, eaau7557 (2018).

    Article  Google Scholar 

  141. Del Dottore, E., Sadeghi, A., Mondini, A. & Mazzolai, B. Continuous growth in plant-inspired robots through 3D additive manufacturing. In Proc. 2018 IEEE International Conference on Robotics and Automation (ICRA) 3454–3460 (IEEE, 2018).

  142. Kenneally, G., De, A. & Koditschek, D. E. Design principles for a family of direct-drive legged robots. IEEE Robot. Autom. Lett. 1, 900–907 (2016).

    Article  Google Scholar 

  143. Chae, S.-H., Baek, S.-M., Lee, J. & Cho, K.-J. Agile and energy-efficient jumping–crawling robot through rapid transition of locomotion and enhanced jumping height adjustment. IEEE/ASME Trans. Mechatron. 27, 5890–5901 (2022).

    Article  Google Scholar 

  144. Kau, N., Schultz, A., Ferrante, N. & Slade, P. Stanford Doggo: an open-source, quasi-direct-drive quadruped. In Proc. 2019 International Conference on Robotics and Automation (ICRA) 6309–6315 (IEEE, 2019).

  145. Bledt, G. et al. MIT Cheetah 3: design and control of a robust, dynamic quadruped robot. In Proc. 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2245–2252 (IEEE, 2018).

  146. Hutter, M. et al. ANYmal - a highly mobile and dynamic quadrupedal robot. In Proc. 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 38–44 (IEEE, 2016).

  147. Spröwitz, A. et al. Towards dynamic trot gait locomotion: design, control, and experiments with Cheetah-cub, a compliant quadruped robot. Int. J. Robot. Res. 32, 932–950 (2013).

    Article  Google Scholar 

  148. Reher, J. P., Hereid, A., Kolathaya, S., Hubicki, C. M. & Ames, A. D. Algorithmic foundations of realizing multi-contact locomotion on the humanoid robot DURUS. In Proc. Algorithmic Foundations of Robotics XII (eds Goldberg, K. et al.) 400–415 (Springer, 2020).

  149. Arrázola-Vásquez, E. et al. Earthworm burrowing modes and rates depend on earthworm species and soil mechanical resistance. Appl. Soil Ecol. 178, 104568 (2022).

    Article  Google Scholar 

  150. Wells, M. J. & Clarke, A. Energetics: the costs of living and reproducing for an individual cephalopod. Philos. Trans. R. Soc. B 351, 1083–1104 (1996).

    Article  Google Scholar 

  151. Hnilička, F. et al. Combustion calorimetry and its application in the assessment of ecosystems. J. Therm. Anal. Calorim. 142, 771–781 (2020).

    Article  Google Scholar 

  152. Yan, P., Xu, L. & He, N. Variation in the calorific values of different plants organs in China. PLoS One 13, e0199762 (2018).

    Article  Google Scholar 

  153. Die Nährwerttabelle 9th edn. Deutsche Gesellschaft für Ernährung https://www.dge.de/presse/meldungen/2024/9-auflage-naehrwerttabelle/ (2024).

  154. Picardi, G., De Luca, M., Chimienti, G., Cianchetti, M. & Calisti, M. User-driven design and development of an underwater soft gripper for biological sampling and litter collection. J. Mar. Sci. Eng. 11, 771 (2023).

    Article  Google Scholar 

  155. Lighton, J. R. B. Minimum cost of transport and ventilatory patterns in three African beetles. Physiol. Zool. 58, 390–399 (1985).

    Article  Google Scholar 

  156. Priest, J. in Encyclopedia of Energy (ed. Cleveland, C. J.) 1–7 (Elsevier, 2004).

  157. Fuentes, M. A. The mechanical cost of transport of fast running animals. J. Theor. Biol. 345, 22–31 (2014).

    Article  Google Scholar 

  158. Beismann, H. et al. Brittleness of twig bases in the genus Salix: fracture mechanics and ecological relevance. J. Exp. Bot. 51, 617–633 (2000).

    Article  Google Scholar 

  159. Beismann, H., Barker, J. H. A., Karp, A. & Speck, T. AFLP analysis sheds light on distribution of two Salix species and their hybrid along a natural gradient. Mol. Ecol. 6, 989–993 (1997).

    Article  Google Scholar 

  160. Acosta-Rangel, A., Rechcigl, J., Bollin, S., Deng, Z. & Agehara, S. Hop (Humulus lupulus L.) phenology, growth, and yield under subtropical climatic conditions: effects of cultivars and crop management. Aust. J. Crop Sci. 15, 764–772 (2021).

    Article  Google Scholar 

  161. Lieth, H. in Application of Calorimetry in Life Sciences (eds Lamprecht, I. & Schaarschmidt, B.) 325–336 (De Gruyter, 1977).

  162. Armour, R. H. & Vincent, J. F. V. Rolling in nature and robotics: a review. J. Bionic Eng. 3, 195–208 (2006).

    Article  Google Scholar 

  163. Flaherty, E. A., Scheibe, J. S. & Goldingay, R. Locomotor performance in the squirrel glider, Petaurus norfolcensis, and the sugar glider, Petaurus breviceps. Aust. Mammal. 30, 25–35 (2008).

    Article  Google Scholar 

  164. Scheibe, J. S., Smith, W. P., Bassham, J. & Magness, D. Locomotor performance and cost of transport in the northern flying squirrel Glaucomys sabrinus. Acta Theriol. 51, 169–178 (2006).

    Article  Google Scholar 

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Acknowledgements

T.S. is grateful for funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC-2193/1 – 390951807. C.L. acknowledges support from the National University of Singapore (NUS) through her start-up Grant RoboLife (Soft Robots with Morphological Adaptation and Life-Like Abilities). B.M. and E.D.D. acknowledge support from the European Research Council under the European Union’s Horizon 2020 research and innovation programme grant agreement No. 101003304 (I-Wood). B.M. acknowledges support from the European Union Horizon 2020 research and innovation programme under grant agreement No 101017940 (I-Seed).

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Authors and Affiliations

  1. Bioinspired Soft Robotics Laboratory, Fondazione Istituto Italiano di Tecnologia, Genova, Italy

    Barbara Mazzolai & Emanuela Del Dottore

  2. Plant Biomechanics Group, Botanic Garden, Faculty of Biology, University of Freiburg and Cluster of Excellence livMatS @ FIT – Freiburg Center for Interactive Materials and Bioinspired Technologies, Freiburg, Germany

    Thomas Speck

  3. AMAP Laboratory, University of Montpellier, CIRAD, CNRS, INRAE, IRD, Montpellier, France

    Nick Rowe

  4. Advanced Robotics Centre and Department of Mechanical Engineering, National University of Singapore, Singapore, Singapore

    Cecilia Laschi

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Mazzolai, B., Del Dottore, E., Speck, T. et al. Energy-saving movement strategies in animals and plants for robot design. Nat Rev Bioeng (2025). https://doi.org/10.1038/s44222-025-00344-z

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