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  • Review Article
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Symbiotic energy paradigm for self-sustaining aerial robots

Nature Reviews Electrical Engineering volume 2, pages 302–319 (2025)Cite this article

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Abstract

Aerial robots, capable of autonomous flight and task execution, are increasingly applied in photography, geo-mapping, surveillance, agriculture and logistics fields. As these technologies evolve, the need for robust, reliable and self-sustaining aerial robots (SSARs) with extended endurance and range becomes more urgent. Integrating energy-harvesting technologies in aerial robots is essential to enable self-sufficiency by using environmental energy sources. The analysis of the design principles of aerial robots and the exploration of energy utilization models from nature that offer symbiotic energy design concepts are essential for creating compact, versatile and efficient SSARs. Here, we discuss the emerging paradigm of environmental energy-harvesting and storage technologies and construct system-level energy matching and analyse flight energy-saving technologies guided by symbiotic energy principles, such as self-sensing, advanced drives, dynamic soaring and swarm intelligence. We also address technical challenges in the evaluation, design and development processes and discuss future directions considering interdisciplinary research in artificial intelligence and advanced materials. Central to this Review is an emphasis on a symbiotic energy design paradigm that integrates bionics, multifunctionality and integration in developing SSARs.

Key points

  • The symbiotic energy paradigm adopts bionic, multifunctional and holistic design strategies to achieve energy autonomy by efficiently harnessing environmental energy.

  • Symbiotic energy leverages nature-inspired energy-harvesting and energy-saving strategies to achieve compact, multifunctional and efficient aerial robot designs.

  • Symbiotic energy systems based on energy-harvesting technologies continuously replenish onboard energy storage by integrating energy harvesting into aerial robot platforms.

  • Symbiotic energy systems based on energy-saving technologies harness environmental energy to sustain operations, including self-sensing, advanced actuation systems, dynamic soaring and swarm intelligence.

  • The widespread adoption of symbiotic energy systems is hindered by the absence of standardized evaluation methods, complexities in system integration and inefficient energy-harvesting techniques.

  • Interdisciplinary research in artificial intelligence and advanced materials is crucial to overcoming challenges and advancing symbiotic energy systems.

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Fig. 1: Nature-inspired symbiotic energy paradigm for self-sustaining aerial robots.
Fig. 2: Existing and potential energy-harvesting technologies for symbiotic energy systems.
Fig. 3: System-level energy matching.
Fig. 4: Existing or potential energy-saving technologies applicable to symbiotic energy systems.
Fig. 5: Outlook for symbiotic energy systems.

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References

  1. Floreano, D. & Wood, R. J. Science, technology and the future of small autonomous drones. Nature 521, 460–466 (2015). This review describes the principles, the technology and the research directions of small autonomous drones.

    Article  Google Scholar 

  2. Zhang, C. et al. Repeatedly programmable liquid crystal dielectric elastomer with multimodal actuation. Adv. Mater. 36, 2313078 (2024).

    Article  Google Scholar 

  3. Randau, S. et al. Benchmarking the performance of all-solid-state lithium batteries. Nat. Energy 5, 259–270 (2020).

    Article  Google Scholar 

  4. Zhang, K. et al. Aerial additive manufacturing with multiple autonomous robots. Nature 609, 709–717 (2022).

    Article  Google Scholar 

  5. Boukoberine, M. N., Zhou, Z. & Benbouzid, M. A critical review on unmanned aerial vehicles power supply and energy management: solutions, strategies, and prospects. Appl. Energy 255, 113823 (2019).

    Article  Google Scholar 

  6. Chen, W. et al. Ultralong cycling and safe lithium–sulfur pouch cells for sustainable energy storage. Adv. Mater. 36, 2312880 (2024).

    Article  Google Scholar 

  7. Dixit, M. et al. Battery electrolyte design for electric vertical takeoff and landing (eVTOL) platforms. Adv. Energy Mater. 14, 2400772 (2024).

    Article  Google Scholar 

  8. Morganti, K. et al. Low carbon transportation fuels: deployment pathways, opportunities and challenges. Energy Environ. Sci. 17, 531–568 (2024).

    Article  Google Scholar 

  9. Gallagher, J. Costing out fuel cells. Nat. Energy 8, 907–907 (2023).

    Article  Google Scholar 

  10. Xu, M., Hu, A. & Wang, H. Visual-impedance-based human–robot cotransportation with a tethered aerial vehicle. IEEE Trans. Ind. Informat. 19, 10356–10365 (2023).

    Article  Google Scholar 

  11. Wang, Y. et al. Organic laser power converter for efficient wireless micro power transfer. Nat. Commun. 14, 5511 (2023).

    Article  Google Scholar 

  12. Shi, J. et al. From garish to practical: synergetic effects of short-circuiting and charge-trapping for high-entropy energy harvesting. Energy Environ. Sci. 17, 5480–5489 (2024).

    Article  Google Scholar 

  13. Lee, Y. H. Beyond the Shockley–Queisser limit: exploring new frontiers in solar energy harvest. Science 383, eado4308 (2024).

    Article  Google Scholar 

  14. Xu, L. et al. Resilience of renewable power systems under climate risks. Nat. Rev. Electr. Eng. 1, 53–66 (2024).

    Article  Google Scholar 

  15. Blaabjerg, F., Chen, M. & Huang, L. Power electronics in wind generation systems. Nat. Rev. Electr. Eng. 1, 234–250 (2024).

    Article  Google Scholar 

  16. 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). This work demonstrates the sustained flight of an insect-sized robot dubbed the RoboBee X-Wing.

    Article  Google Scholar 

  17. Bang, J. et al. Bioinspired electronics for intelligent soft robots. Nat. Rev. Electr. Eng. 1, 597–613 (2024).

    Article  Google Scholar 

  18. Soudi, N., Nanayakkara, S., Jahed, N. M. S. & Naahidi, S. Rise of nature-inspired solar photovoltaic energy convertors. Sol. Energy 208, 31–45 (2020).

    Article  Google Scholar 

  19. Zhao, W. et al. Effect of self-cleaning superhydrophobic coating on dust deposition and performance of PV modules. Renew. Energ. 227, 120576 (2024).

    Article  Google Scholar 

  20. Tadepalli, S., Slocik, J. M., Gupta, M. K., Naik, R. R. & Singamaneni, S. Bio-optics and bio-inspired optical materials. Chem. Rev. 117, 12705–12763 (2017).

    Article  Google Scholar 

  21. Wilson, J. A. Sweeping flight and soaring by albatrosses. Nature 257, 307–308 (1975). This work introduces a suitable method, dynamic soaring, to account for the sweeping flight and soaring by albatrosses.

    Article  Google Scholar 

  22. Leitch, K. J., Ponce, F. V., Dickson, W. B., van Breugel, F. & Dickinson, M. H. The long-distance flight behavior of Drosophila supports an agent-based model for wind-assisted dispersal in insects. Proc. Natl Acad. Sci. USA 118, e2013342118 (2021).

    Article  Google Scholar 

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

    Article  Google Scholar 

  24. der Weduwen, D. & Ruxton, G. D. Secondary dispersal mechanisms of winged seeds: a review. Biol. Rev. 94, 1830–1838 (2019).

    Article  Google Scholar 

  25. Bami Chatenet, Y. & Valette, S. Elucidating the lotus and rose-petal effects on hierarchical surfaces: study of the effect of topographical scales on the contact angle hysteresis. J. Colloid Interface Sci. 676, 355–367 (2024).

    Article  Google Scholar 

  26. Li, X. et al. A self-charging device with bionic self-cleaning interface for energy harvesting. Nano Energy 73, 104738 (2020).

    Article  Google Scholar 

  27. Zhang, B. et al. Nature-inspired interfacial engineering for energy harvesting. Nat. Rev. Electr. Eng. 1, 218–233 (2024). This work explores diverse energy-harvesting processes in nature to establish a fundamental understanding of nature’s strategies.

    Article  Google Scholar 

  28. Aubin, C. A. et al. Towards enduring autonomous robots via embodied energy. Nature 602, 393–402 (2022). This review examines how system integration and multifunctionality in nature inspire a new paradigm for autonomous robots, embodied energy.

    Article  Google Scholar 

  29. Sihite, E. & Ramezani, A. A morphology-centered view towards describing bats dynamically versatile wing conformations. Int. J. Rob. Res. 0, 02783649241272132 (2024).

    Google Scholar 

  30. Weimerskirch, H., Martin, J., Clerquin, Y., Alexandre, P. & Jiraskova, S. Energy saving in flight formation. Nature 413, 697–698 (2001).

    Article  Google Scholar 

  31. Chang, J. et al. A dragonfly-wing-like energy harvester with enhanced magneto-mechano-electric coupling. Device 1, 100021 (2023).

    Article  Google Scholar 

  32. Ozaki, T., Ohta, N., Jimbo, T. & Hamaguchi, K. A wireless radiofrequency-powered insect-scale flapping-wing aerial vehicle. Nat. Electron. 4, 845–852 (2021). This work presents a wireless radio frequency power supply that can drive an insect-scale flapping-wing aerial vehicle.

    Article  Google Scholar 

  33. Yin, L., Kim, K. N., Trifonov, A., Podhajny, T. & Wang, J. Designing wearable microgrids: towards autonomous sustainable on-body energy management. Energy Environ. Sci. 15, 82–101 (2022).

    Article  Google Scholar 

  34. Ahmad, F. F., Ghenai, C. & Bettayeb, M. Maximum power point tracking and photovoltaic energy harvesting for internet of things: a comprehensive review. Sustain. Energy Technol. Assess. 47, 101430 (2021).

    Google Scholar 

  35. Shen, W. et al. Sunlight-powered sustained flight of an ultralight micro aerial vehicle. Nature 631, 537–543 (2024). This work introduces an electrostatic flyer to realize solar-powered sustained flight of a micro aerial vehicle under natural sunlight conditions.

    Article  Google Scholar 

  36. Hailegnaw, B. et al. Flexible quasi-2D perovskite solar cells with high specific power and improved stability for energy-autonomous drones. Nat. Energy 9, 677–690 (2024).

    Article  Google Scholar 

  37. Ridwan, I. & Alfindo. The effect of use of solar panels on micro scale fixed-wing UAV type as a power recharging system. AIP Conf. Proc. 2180, 020044 (2019).

    Article  Google Scholar 

  38. Perez-Rosado, A., Gehlhar, R. D., Nolen, S., Gupta, S. K. & Bruck, H. A. Design, fabrication, and characterization of multifunctional wings to harvest solar energy in flapping wing air vehicles. Smart Mater. Struct. 24, 065042 (2015).

    Article  Google Scholar 

  39. Mao, P. et al. Single-step-fabricated disordered metasurfaces for enhanced light extraction from LEDs. Light Sci. Appl. 10, 180 (2021).

    Article  Google Scholar 

  40. Luo, M., Tarasov, A., Zhang, H. & Chu, J. Hybrid perovskites unlocking the development of light-emitting solar cells. Nat. Rev. Mater. 9, 295–297 (2024).

    Article  Google Scholar 

  41. Brinkmann, K. O. et al. Perovskite–organic tandem solar cells. Nat. Rev. Mater. 9, 202–217 (2024).

    Article  Google Scholar 

  42. Massiot, I., Cattoni, A. & Collin, S. Progress and prospects for ultrathin solar cells. Nat. Energy 5, 959–972 (2020).

    Article  Google Scholar 

  43. Hasan, M. A. M., Zhu, W., Bowen, C. R., Wang, Z. L. & Yang, Y. Triboelectric nanogenerators for wind energy harvesting. Nat. Rev. Electr. Eng. 1, 453–465 (2024). This work introduces the technological advancement of wind-driven triboelectric nanogenerators, starting from a detailed comparison with conventional wind turbine systems.

    Article  Google Scholar 

  44. Wei, X., Yi, Z., Li, W., Zhao, L. & Zhang, W. Energy harvesting fueling the revival of self-powered unmanned aerial vehicles. Energy Convers. Manage. 283, 116863 (2023).

    Article  Google Scholar 

  45. Yan, Y. et al. Triboelectric-electromagnetic hybrid generator with swing-blade structures for effectively harvesting distributed wind energy in urban environments. Nano Res. 16, 11621–11629 (2023).

    Article  Google Scholar 

  46. O’Connell, M. et al. Neural-Fly enables rapid learning for agile flight in strong winds. Sci. Robot. 7, eabm6597 (2022).

    Article  Google Scholar 

  47. Misseroni, D. et al. Origami engineering. Nat. Rev. Methods Primers 4, 40 (2024).

    Article  Google Scholar 

  48. Long, H. et al. Highly durable and efficient power management friction energy harvester. Nano Energy 123, 109363 (2024).

    Article  Google Scholar 

  49. Jiao, P., Hasni, H., Lajnef, N. & Alavi, A. H. Mechanical metamaterial piezoelectric nanogenerator (MM-PENG): design principle, modeling and performance. Mater. Des. 187, 108214 (2020).

    Article  Google Scholar 

  50. Sun, H., Yang, B. & Zhang, M. Functional–structural integrated aramid nanofiber-based honeycomb materials with ultrahigh strength and multi-functionalities. Adv. Fiber Mater. 6, 1122–1137 (2024).

    Article  Google Scholar 

  51. Tao, K. et al. Hierarchical honeycomb-structured electret/triboelectric nanogenerator for biomechanical and morphing wing energy harvesting. Nano-micro Lett. 13, 123 (2021).

    Article  Google Scholar 

  52. Hou, K., Tan, T., Wang, Z., Wang, B. & Yan, Z. Scarab beetle‐inspired embodied‐energy membranous‐wing robot with flapping‐collision piezo‐mechanoreception and mobile environmental monitoring. Adv. Funct. Mater. 34, 2303745 (2024).

    Article  Google Scholar 

  53. Wang, B. et al. Woodpecker-mimic two-layer band energy harvester with a piezoelectric array for powering wrist-worn wearables. Nano Energy 89, 106385 (2021).

    Article  Google Scholar 

  54. Son, J., Kim, H., Choi, Y. & Lee, H. 3D printed energy devices: generation, conversion, and storage. Microsyst. Nanoeng. 10, 93 (2024).

    Article  Google Scholar 

  55. Zaiser, M. & Zapperi, S. Disordered mechanical metamaterials. Nat. Rev. Phys. 5, 679–688 (2023).

    Article  Google Scholar 

  56. Xia, X., Spadaccini, C. M. & Greer, J. R. Responsive materials architected in space and time. Nat. Rev. Mater. 7, 683–701 (2022).

    Article  Google Scholar 

  57. Xu, X. et al. Droplet energy harvesting panel. Energy Environ. Sci. 15, 2916–2926 (2022).

    Article  Google Scholar 

  58. Ye, C. et al. A hydrophobic self-repairing power textile for effective water droplet energy harvesting. ACS Nano 15, 18172–18181 (2021).

    Article  Google Scholar 

  59. Zhang, P. et al. Biomimetic superhydrophobic triboelectric surface prepared by interfacial self‐assembly for water harvesting. Adv. Funct. Mater. 35, 2413201 (2025).

    Article  Google Scholar 

  60. Zeng, S. et al. Hierarchical-morphology metafabric for scalable passive daytime radiative cooling. Science 373, 692–696 (2021).

    Article  Google Scholar 

  61. Xu, J. et al. A durable, breathable, and weather-adaptive coating driven by particle self-assembly for radiative cooling and energy harvesting. Nano Energy 124, 109489 (2024).

    Article  Google Scholar 

  62. Liu, M., Wang, S. & Jiang, L. Nature-inspired superwettability systems. Nat. Rev. Mater. 2, 17036 (2017).

    Article  Google Scholar 

  63. Zhang, S. et al. Standalone stretchable RF systems based on asymmetric 3D microstrip antennas with on-body wireless communication and energy harvesting. Nano Energy 96, 107069 (2022).

    Article  Google Scholar 

  64. Zaeimbashi, M. et al. Ultra-compact dual-band smart NEMS magnetoelectric antennas for simultaneous wireless energy harvesting and magnetic field sensing. Nat. Commun. 12, 3141 (2021).

    Article  Google Scholar 

  65. Luo, B. et al. Magnetoelectric microelectromechanical and nanoelectromechanical systems for the IoT. Nat. Rev. Electr. Eng. 1, 317–334 (2024).

    Article  Google Scholar 

  66. Ye, C. et al. An integrated solar panel with a triboelectric nanogenerator array for synergistic harvesting of raindrop and solar energy. Adv. Mater. 35, 2209713 (2023).

    Article  Google Scholar 

  67. Guo, J. et al. Boosting the power conversion efficiency of hybrid triboelectric-photovoltaic cells through the field coupling effect. Device 3, 100562 (2025).

    Article  Google Scholar 

  68. Min, G. et al. Multisource energy harvester on textile and plants for clean energy generation from wind and rainwater droplets. ACS Sustain. Chem. Eng. 12, 695–705 (2024).

    Article  Google Scholar 

  69. Kou, Z. et al. Wearable all-fabric hybrid energy harvester to simultaneously harvest radiofrequency and triboelectric energy. Adv. Sci. 11, 2309050 (2024).

    Article  Google Scholar 

  70. Roh, H., Kim, I. & Kim, D. Ultrathin unified harvesting module capable of generating electrical energy during rainy, windy, and sunny conditions. Nano Energy 70, 104515 (2020).

    Article  Google Scholar 

  71. Xu, C., Wang, X. & Wang, Z. L. Nanowire structured hybrid cell for concurrently scavenging solar and mechanical energies. J. Am. Chem. Soc. 131, 5866–5872 (2009).

    Article  Google Scholar 

  72. Xiao, X. et al. Mechanics and electrochemistry in nature-inspired functional batteries: fundamentals, configurations and devices. Energy Environ. Sci. 17, 974–1006 (2024).

    Article  Google Scholar 

  73. Li, L. et al. Advanced multifunctional aqueous rechargeable batteries design: from materials and devices to systems. Adv. Mater. 34, 2104327 (2022).

    Article  Google Scholar 

  74. Wang, M. et al. Biomorphic structural batteries for robotics. Sci. Robot. 5, eaba1912 (2020).

    Article  Google Scholar 

  75. Wang, M. et al. Biomimetic solid-state Zn2+ electrolyte for corrugated structural batteries. ACS Nano 13, 1107–1115 (2019).

    Google Scholar 

  76. Liu, R., Wang, Z. L., Fukuda, K. & Someya, T. Flexible self-charging power sources. Nat. Rev. Mater. 7, 870–886 (2022).

    Article  Google Scholar 

  77. Zhu, T. et al. Wireless portable light-weight self-charging power packs by perovskite-organic tandem solar cells integrated with solid-state asymmetric supercapacitors. Nano Energy 78, 105397 (2020).

    Article  Google Scholar 

  78. Gervillié-Mouravieff, C., Bao, W., Steingart, D. A. & Meng, Y. S. Non-destructive characterization techniques for battery performance and life-cycle assessment. Nat. Rev. Electr. Eng. 1, 547–558 (2024).

    Article  Google Scholar 

  79. Yao, Y. et al. Arc-shaped flutter-driven wind speed sensor based on triboelectric nanogenerator for unmanned aerial vehicle. Nano Energy 104, 107871 (2022).

    Article  Google Scholar 

  80. Li, Z. et al. A droplet-based electricity generator for large-scale raindrop energy harvesting. Nano Energy 100, 107443 (2022).

    Article  Google Scholar 

  81. Wu, H. et al. Efficient energy conversion mechanism and energy storage strategy for triboelectric nanogenerators. Nat. Commun. 15, 6558 (2024).

    Article  Google Scholar 

  82. Cansiz, M., Altinel, D. & Kurt, G. K. Efficiency in RF energy harvesting systems: a comprehensive review. Energy 174, 292–309 (2019).

    Article  Google Scholar 

  83. Lai, Z., Xu, J., Bowen, C. R. & Zhou, S. Self-powered and self-sensing devices based on human motion. Joule 6, 1501–1565 (2022).

    Article  Google Scholar 

  84. Xie, X. et al. Self‐powered gyroscope angle sensor based on resistive matching effect of triboelectric nanogenerator. Adv. Mater. Technol. 6, 2100797 (2021).

    Article  Google Scholar 

  85. Zhou, Z. et al. Triboelectricity based self‐powered digital displacement sensor for aircraft flight actuation. Adv. Funct. Mater. 34, 2311839 (2024). This work develops a self-powered displacement sensor to monitor the position status of the flight actuators in unmanned aerial vehicles.

    Article  Google Scholar 

  86. Sheng, H. et al. Self‐powered digital angle sensor based on triboelectric signal for variable structure of aircraft. Adv. Mater. Technol. 9, 2301708 (2024).

    Article  Google Scholar 

  87. Liu, Y. et al. A bioinspired triboelectric wireless anemometer with low cut-in wind speed for meteorological UAVs. Nano Energy 128, 109917 (2024).

    Article  Google Scholar 

  88. Guan, X. et al. Wireless online rotation monitoring system for UAV motors based on a soft-contact triboelectric nanogenerator. ACS Appl. Mater. Interfaces 16, 46516–46526 (2024).

    Article  Google Scholar 

  89. Li, Q., Tan, T., Wang, B. & Yan, Z. Avian-inspired embodied perception in biohybrid flapping-wing robotics. Nat. Commun. 15, 9099 (2024).

    Article  Google Scholar 

  90. Shin, H.-S. et al. Bio-inspired large-area soft sensing skins to measure UAV wing deformation in flight. Adv. Funct. Mater. 31, 2100679 (2021).

    Article  Google Scholar 

  91. Yang, Z. et al. A vision chip with complementary pathways for open-world sensing. Nature 629, 1027–1033 (2024).

    Article  Google Scholar 

  92. Jiao, P. et al. Mechanical metamaterials and beyond. Nat. Commun. 14, 6004 (2023).

    Article  Google Scholar 

  93. Wu, B. et al. Functional materials for powering and implementing next-generation miniature sensors. Mater. Today 69, 333–354 (2023).

    Article  Google Scholar 

  94. Liu, H. et al. Bioinspired multifunctional self-sensing actuated gradient hydrogel for soft–hard robot remote interaction. Nano-Micro Lett. 16, 69 (2024).

    Article  Google Scholar 

  95. Chen, D. et al. 4D printing strain self-sensing and temperature self-sensing integrated sensor–actuator with bioinspired gradient gaps. Adv. Sci. 7, 2000584 (2020).

    Article  Google Scholar 

  96. Ozaki, T. & Ohta, N. Power-efficient driver circuit for piezo electric actuator with passive charge recovery. Energies 13, 2866 (2020).

    Article  Google Scholar 

  97. Wood, R. J. The first takeoff of a biologically inspired at-scale robotic insect. IEEE Trans. Robot. 24, 341–347 (2008).

    Article  Google Scholar 

  98. James, J., Iyer, V., Chukewad, Y., Gollakota, S. & Fuller, S. B. Liftoff of a 190 mg laser-powered aerial vehicle: the lightest wireless robot to fly. In 2018 IEEE International Conference on Robotics and Automation (ICRA) 3587–3594 (IEEE, 2018).

  99. Liu, Z., Yan, X., Qi, M., Zhang, X. & Lin, L. Low-voltage electromagnetic actuators for flapping-wing micro aerial vehicles. Sens. Actuator A Phys. 265, 1–9 (2017).

    Article  Google Scholar 

  100. Yang, L., Wang, H., Zhang, D., Yang, Y. & Leng, D. Large deformation, high energy density dielectric elastomer actuators: principles, factors, optimization, applications, and prospects. Chem. Eng. J. 489, 151402 (2024).

    Article  Google Scholar 

  101. Chen, Y. et al. Controlled flight of a microrobot powered by soft artificial muscles. Nature 575, 324–329 (2019).

    Article  Google Scholar 

  102. Helps, T., Romero, C., Taghavi, M., Conn, A. T. & Rossiter, J. Liquid-amplified zipping actuators for micro-air vehicles with transmission-free flapping. Sci. Robot. 7, eabi8189 (2022). This work describes an actuation system for flapping micro-air vehicles called the liquid-amplified zipping actuator.

    Article  Google Scholar 

  103. Kim, S. et al. Laser-assisted failure recovery for dielectric elastomer actuators in aerial robots. Sci. Robot. 8, eadf4278 (2023).

    Article  Google Scholar 

  104. Pilz Da Cunha, M., Debije, M. G. & Schenning, A. P. H. J. Bioinspired light-driven soft robots based on liquid crystal polymers. Chem. Soc. Rev. 49, 6568–6578 (2020).

    Article  Google Scholar 

  105. Wu, X. et al. Light-driven microdrones. Nat. Nanotechnol. 17, 477–484 (2022). This work demonstrates light-driven microdrones in an aqueous environment.

    Article  Google Scholar 

  106. Wang, D. et al. Bioinspired rotary flight of light-driven composite films. Nat. Commun. 14, 5070 (2023).

    Article  Google Scholar 

  107. Vo Doan, T. T. & Sato, H. Insect–machine hybrid system: remote radio control of a freely flying beetle (Mercynorrhina torquata). J. Vis. Exp. 115, 54260 (2016).

    Google Scholar 

  108. Vo Doan, T. T., Li, Y., Cao, F. & Sato, H. Cyborg beetle: thrust control of free flying beetle via a miniature wireless neuromuscular stimulator. In 2015 28th IEEE International Conference on Micro Electro Mechanical Systems (MEMS) 1048–1050 (2015).

  109. Vo-Doan, T. T., Dung, V. T. & Sato, H. A cyborg insect reveals a function of a muscle in free flight. Cyborg Bionic Syst. 2022, 9780504 (2022).

    Article  Google Scholar 

  110. Zhou, Z. et al. Pigeon robot for navigation guided by remote control: system construction and functional verification. J. Bionic Eng. 18, 184–196 (2021).

    Article  Google Scholar 

  111. Aktakka, E. E., Kim, H. & Najafi, K. Energy scavenging from insect flight. J. Micromech. Microeng. 21, 095016 (2011).

    Article  Google Scholar 

  112. Phan, H.-V., Park, H. C. & Floreano, D. Passive wing deployment and retraction in beetles and flapping microrobots. Nature 632, 1067–1072 (2024).

    Article  Google Scholar 

  113. Farisenkov, S. E. et al. Novel flight style and light wings boost flight performance of tiny beetles. Nature 602, 96–100 (2022).

    Article  Google Scholar 

  114. Bai, S., He, Q. & Chirarattananon, P. A bioinspired revolving-wing drone with passive attitude stability and efficient hovering flight. Sci. Robot. 7, eabg5913 (2022). This work introduces a bioinspired revolving-wing drone with passive attitude stability and efficient hovering flight.

    Article  Google Scholar 

  115. Ajanic, E., Feroskhan, M., Mintchev, S., Noca, F. & Floreano, D. Bioinspired wing and tail morphing extends drone flight capabilities. Sci. Robot. 5, eabc2897 (2020).

    Article  Google Scholar 

  116. Harvey, C. & Inman, D. J. Gull dynamic pitch stability is controlled by wing morphing. Proc. Natl Acad. Sci. USA 119, e2204847119 (2022).

    Article  Google Scholar 

  117. Wang, W., An, W. & Song, B. Effect of wing morphing on stability and energy harvesting in albatross dynamic soaring. Chin. J. Aeronaut. 37, 317–334 (2024).

    Article  Google Scholar 

  118. Mir, I., Taha, H., Eisa, S. A. & Maqsood, A. A controllability perspective of dynamic soaring. Nonlinear Dynam. 94, 2347–2362 (2018).

    Article  Google Scholar 

  119. Reddy, G., Celani, A., Sejnowski, T. J. & Vergassola, M. Learning to soar in turbulent environments. Proc. Natl Acad. Sci. USA 113, E4877–E4884 (2016).

    Article  Google Scholar 

  120. Chin, Y.-W. et al. Efficient flapping wing drone arrests high-speed flight using post-stall soaring. Sci. Robot. 5, eaba2386 (2020).

    Article  Google Scholar 

  121. Zhu, B., Zhu, J. & Chen, Q. A bio-inspired flight control strategy for a tail-sitter unmanned aerial vehicle. Sci. China Inf. Sci. 63, 170203 (2020).

    Article  Google Scholar 

  122. Duan, H., Huo, M. & Fan, Y. From animal collective behaviors to swarm robotic cooperation. Natl Sci. Rev. 10, nwad040 (2023). This article reviews several typical natural collective behaviours and introduces the origin and connotation of swarm intelligence.

    Article  Google Scholar 

  123. Wang, Y. & Wang, D. Tight formation control of multiple unmanned aerial vehicles through an adaptive control method. Sci. China Inf. Sci. 60, 070207 (2017).

    Article  Google Scholar 

  124. Usov, D., Chronis, T., Ardelean, I.-C. & Filippone, A. On minimum power flight formations of lifting propellers. Aerosp. Sci. Technol. 149, 109150 (2024).

    Article  Google Scholar 

  125. Newbolt, J. W. et al. Flow interactions lead to self-organized flight formations disrupted by self-amplifying waves. Nat. Commun. 15, 3462 (2024).

    Article  Google Scholar 

  126. Chen, K. & Zhang, Z. In-flight wireless charging: a promising application-oriented charging technique for drones. IEEE Ind. Electron. Mag. 18, 6–16 (2024).

    Article  Google Scholar 

  127. Chen, K. & Zhang, Z. Rotating-coordinate-based mutual inductance estimation for drone in-flight wireless charging systems. IEEE Trans. Power Electron. 38, 11685–11693 (2023).

    Article  Google Scholar 

  128. Ma, X., Liu, X. & Ansari, N. Green laser-powered UAV far-field wireless charging and data backhauling for a large-scale sensor network. IEEE Internet Things J. 11, 31932–31946 (2024).

    Article  Google Scholar 

  129. Wang, Z., Lv, T., Zeng, J. & Ni, W. Placement and resource allocation of wireless-powered multiantenna UAV for energy-efficient multiuser NOMA. IEEE Trans. Wirel. Commun. 21, 8757–8771 (2022).

    Article  Google Scholar 

  130. Murshed, S. et al. Weighted fair energy transfer in a UAV network: a multi-agent deep reinforcement learning approach. Energy 292, 130527 (2024).

    Article  Google Scholar 

  131. Lee, S., Yu, H. & Lee, H. Multiagent Q-learning-based multi-UAV wireless networks for maximizing energy efficiency: deployment and power control strategy design. IEEE Internet Things J. 9, 6434–6442 (2022).

    Article  Google Scholar 

  132. Quan, L. et al. Robust and efficient trajectory planning for formation flight in dense environments. IEEE Trans. Robot. 39, 4785–4804 (2023).

    Article  Google Scholar 

  133. Zhu, X., Zhai, L., Li, N., Li, Y. & Yang, F. Multi-objective deployment optimization of UAVs for energy-efficient wireless coverage. IEEE Trans. Commun. 72, 3587–3601 (2024).

    Article  Google Scholar 

  134. Johannisson, W. et al. A residual performance methodology to evaluate multifunctional systems. Multifunct. Mater. 3, 025002 (2020).

    Article  Google Scholar 

  135. Berjawi, A. E. H., Walker, S. L., Patsios, C. & Hosseini, S. H. R. An evaluation framework for future integrated energy systems: a whole energy systems approach. Renew. Sustain. Energy Rev. 145, 111163 (2021).

    Article  Google Scholar 

  136. Jay, C. et al. Prioritize environmental sustainability in use of AI and data science methods. Nat. Geosci. 17, 106–108 (2024).

    Article  Google Scholar 

  137. Luo, H. et al. A survey on causal inference for recommendation. Innov. 5, 100590 (2024).

    Google Scholar 

  138. Burden, S. A., Libby, T., Jayaram, K., Sponberg, S. & Donelan, J. M. Why animals can outrun robots. Sci. Robot. 9, eadi9754 (2024). This review discusses why animals outrun robots in agility, range and robustness.

    Article  Google Scholar 

  139. Lu, K., Shim, J., Kim, K. S., Kim, S. W. & Kim, J. 2D materials can unlock single-crystal-based monolithic 3D integration. Nat. Electron. 7, 416–418 (2024).

    Article  Google Scholar 

  140. Graziosi, S. et al. A vision for sustainable additive manufacturing. Nat. Sustain. 7, 698–705 (2024).

    Article  Google Scholar 

  141. Zheng, L., Karapiperis, K., Kumar, S. & Kochmann, D. M. Unifying the design space and optimizing linear and nonlinear truss metamaterials by generative modeling. Nat. Commun. 14, 7563 (2023).

    Article  Google Scholar 

  142. Qi, L. et al. Recent progress in application‐oriented self‐powered microelectronics. Adv. Energy Mater. 13, 2302699 (2023).

    Article  Google Scholar 

  143. Wang, Z. L. & Wang, A. C. On the origin of contact-electrification. Mater. Today 30, 34–51 (2019).

    Article  Google Scholar 

  144. Zhou, M., Sheng, Z., Ji, G. & Zhang, X. Aerogel‐involved triple‐state gels resemble natural living leaves in structure and multi‐functions. Adv. Mater. 36, 2406007 (2024).

    Article  Google Scholar 

  145. Liu, X. et al. Power generation from ambient humidity using protein nanowires. Nature 578, 550–554 (2020).

    Article  Google Scholar 

  146. Wang, P. et al. Nanoarchitectonics in advanced membranes for enhanced osmotic energy harvesting. Adv. Mater. 36, 2404418 (2024).

    Article  Google Scholar 

  147. Kong, L. et al. A self-powered and self-sensing lower-limb system for smart healthcare. Adv. Energy Mater. 13, 2301254 (2023).

    Article  Google Scholar 

  148. Zhou, H. et al. Structural composite energy storage devices — a review. Mater. Today Energy 24, 100924 (2022).

    Article  Google Scholar 

  149. Zhu, M. et al. Efficient energy management for intelligent microrobotic swarms: design and impact. Adv. Energy Mater. 14, 2400881 (2024).

    Article  Google Scholar 

  150. Mitchell, M. Debates on the nature of artificial general intelligence. Science 383, eado7069 (2024).

    Article  Google Scholar 

  151. Gschwendtner, M., Soller, H. & Zingg, S. Combining quantum and AI for the next superpower. Nat. Rev. Electr. Eng. 1, 350–351 (2024).

    Article  Google Scholar 

  152. Fei, N. et al. Towards artificial general intelligence via a multimodal foundation model. Nat. Commun. 13, 3094 (2022).

    Article  Google Scholar 

  153. Zhang, P., Wang, D. & Lu, H. Multi-modal visual tracking: review and experimental comparison. Comp. Vis. Media 10, 193–214 (2024).

    Article  Google Scholar 

  154. Xu, Z. Soft nanofluidic machinery. ACS Nano 18, 9765–9772 (2024).

    Article  Google Scholar 

  155. Ru, X. et al. Silicon heterojunction solar cells achieving 26.6% efficiency on commercial-size p-type silicon wafer. Joule 8, 1092–1104 (2024).

    Article  Google Scholar 

  156. Wang, L. & Li, R. W. A more biofriendly piezoelectric material. Science 383, 1416–1416 (2024).

    Article  Google Scholar 

  157. Cheng, T., Shao, J. & Wang, Z. L. Triboelectric nanogenerators. Nat. Rev. Methods Primers 3, 39 (2023).

    Article  Google Scholar 

  158. Schmaltz, T. et al. A roadmap for solid‐state batteries. Adv. Energy Mater. 13, 2301886 (2023).

    Article  Google Scholar 

  159. Meng, Q., Huang, Y., Li, L., Wu, F. & Chen, R. Smart batteries for powering the future. Joule 8, 344–373 (2024).

    Article  Google Scholar 

  160. Xue, J. et al. New carbon materials for multifunctional soft electronics. Adv. Mater. 37, 2312596 (2025).

    Article  Google Scholar 

  161. Mohanty, A. K. et al. Biocarbon materials. Nat. Rev. Methods Primers 4, 19 (2024).

    Article  Google Scholar 

  162. Yang, L. et al. Electrochemically-driven actuators: from materials to mechanisms and from performance to applications. Chem. Soc. Rev. 53, 5956–6010 (2024).

    Article  Google Scholar 

  163. Li, J. et al. Recent advances in flexible self-oscillating actuators. eScience 4, 100250 (2024).

    Article  Google Scholar 

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Acknowledgements

This work was supported by the National Natural Foundation of China under grant 51975490 and by the Science and Technology Projects of Sichuan under grants 23QYCX0280 and 2022NSFSC0461; and by the Science and Technology Projects of Yibin under grants 2021ZYCG017, 2023SJXQYBKJJH005, SWJTU2021020001 and SWJTU2021020002; and by the Chengdu Science and Technology Projects under grant 2021YF0800138GX.

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Author notes

  1. These authors contributed equally: Hao Wang, Lingji Kong.

Authors and Affiliations

  1. School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China

    Hao Wang, Lingji Kong, Zheng Fang, Zutao Zhang & Qianqian Zong

  2. Yibin Research Institute, Southwest Jiaotong University, Yibin, China

    Hao Wang, Lingji Kong, Zheng Fang, Rui Zou & Xinyi Zhao

  3. School of Design, Southwest Jiaotong University, Chengdu, China

    Rui Zou

  4. Chengdu Technological University, Chengdu, China

    Zutao Zhang

  5. Tangshan Research Institute, Southwest Jiaotong University, Tangshan, China

    Xinyi Zhao

  6. School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, China

    Zhongqu Xie

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Contributions

H.W. and L.K. contributed to the discussion of the content. H.W., L.K. and Z.F. wrote the manuscript. All the authors reviewed and edited the manuscript before submission.

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Correspondence to Zutao Zhang.

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Glossary

Dynamic soaring

A flight technique in which birds or aircraft exploit wind speed gradients between air layers to gain energy and sustain flight with minimal energy consumption.

Energy density

The amount of energy stored per unit mass or volume, commonly used to describe the capacity of batteries or fuels.

Energy efficiency

The capability of aerial robots to minimize energy consumption while maximizing operational performance and endurance.

Energy-harvesting

The process of capturing and converting ambient energy from the environment into usable electrical power for aerial robots.

High-entropy energy

Low-amplitude, low-frequency and low-density energy that is widely dispersed throughout the environment.

Lift-to-drag ratio

In aerodynamics, the ratio of lift-to-aerodynamic drag for an aerofoil or aerial robot, indicating aerodynamic efficiency under given flight conditions.

Lift-to-weight ratio

The ratio of an actuator’s maximum thrust to its weight under standard atmospheric conditions at ground level, indicating its thrust-generating capability relative to its own weight.

Power density

The rate of energy release or consumption per unit mass or volume, indicating how quickly a system can deliver or utilize energy.

Swarm intelligence

The collective, decentralized behaviour of self-organized systems, inspired by social insects such as ants and bees.

Wake capture mechanism

An aerodynamic strategy in which flying organisms or aerial robots reduce energy consume by harvesting vortices generated by preceding entities.

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Wang, H., Kong, L., Fang, Z. et al. Symbiotic energy paradigm for self-sustaining aerial robots. Nat Rev Electr Eng 2, 302–319 (2025). https://doi.org/10.1038/s44287-025-00168-4

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