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Power and control remain major barriers to the realization of untethered autonomous robots that can move and adapt on demand for long duration missions. A close synergy between active systems is needed to optimally use the, often limited, onboard energy supply. Recent examples highlight a pathway towards improved operational lifetimes through the co-integration of chemical and electrical energy sources with mechanical systems to provide robots with high energy and power density1,2,3,4,5. By housing the energy supply directly within the robot’s architecture and materials, it is readily available for use, can be efficiently converted into useful work and, ideally, can be replenished through onboard energy-harvesting mechanisms. We call this design philosophy Embodied Energy, in which the same mass that normally provides a vital mechanical or structural function also contains stored energy that powers at least a portion of the robot or device.

The potential of Embodied Energy systems can be evaluated through biological analogy. In humans and other animals, energy is primarily stored in the body as fat. However, the functionalities of adipose tissue extend far beyond energy storage, to include insulation, the protection of vital organs, waterproofing, and the regulation and production of hormones. ‘Embodied Energy’ can similarly imbue robotic systems with multifunctionality. For example, batteries can be configured to serve load-bearing or architectural functions. Compliant materials and actuators can provide structure while storing and reusing elastic energy.

Over the past two decades, there has been a small, but growing, effort to improve machine autonomy by developing multifunctional, Embodied Energy systems4,5. Most robots, however, still contain isolated power, actuation, sensory and control blocks, each optimized for an individual task1,3,6,7,8 (Fig. 1). In Honda’s ASIMO robot, for example, there is a clear division between the actuators in the joints, the control module in the torso and the batteries in the backpack unit6. Such isolated building blocks lack the synergy and efficiency observed in living organisms (for example, the pictured octopus), which are capable of harvesting, storing and generating energy either continuously or on demand. By distributing energy sources throughout multifunctional system configurations, as illustrated by the progression of innovative robots and their corresponding block diagrams in Fig. 1, we can expand their range of complex functions while increasing their operational efficiency.

Fig. 1: Energy, control and actuating systems in modern robots.
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Energy-storage elements are highlighted in yellow, control elements are highlighted in green and actuators are highlighted in red for each robot. a, The ASIMO humanoid robot6. b, A multigait, quadrupedal soft robot powered by a pneumatic tether7. c, An eight-degree-of-freedom walking robot with embedded actuator sequencing and a single pneumatic input8. d, An untethered octopus-inspired robot controlled by microfluidic logic and powered by the decomposition of a monopropellant fuel that produces pneumatic actuation3. e, An untethered aquatic soft robot with a redox flow battery-inspired vascular system that produces electrical energy and hydraulic actuation1. f, The common octopus. *To provide a direct comparison with mobile robots a–e, we have highlighted the primary actuators of the octopus: the tentacles. Note that there are secondary actuation and sensory/control capabilities not depicted in this simplistic representation. a, Photograph reproduced with permission from ref. 150. f, Photograph credit: Mark Conlin/VWPics/Alamy.

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Energy storage and conversion

An important aspect of Embodied Energy design is precisely how this energy is harvested, stored, applied and recovered throughout the robotic system. Most untethered robot designs are guided by a simple trade-off between size, weight and power. However, by broadening the range of functionalities concurrent in a material or subsystem and distributing the mass budgets between them, we can upend the conventional energy budget and design methodology. Power, sensing, computation and control will be largely native to the mechanical system.

Energy harvesting in robots, itself a burgeoning area of research, warrants its own separate review due to the vast scope of the topic. Some additional consideration can be afforded here in the context of Embodied Energy. The state of the art in energy-harvesting methods (for example, thermal, solar, vibration/kinetic and radio waves) is well established in the literature9,10,11,12,13,14, but existing technologies fall far short in producing enough power to independently operate a typical robot (maximum length, l > 1 m). Even in smaller systems, harvesting the minimum energy required for actuation can impose specific positioning and alignment conditions within the environment, which can constrain device utility and control15. Many researchers instead see energy harvesters as being valuable in complementary applications in which the microwatt to milliwatt power outputs can reliably operate low-power sensors. These sensors could, for example, enable advanced levels of control in robot swarms or spatial sensing in robotic exosuits.

Figure 2 details concepts that are important to consider when designing for Embodied Energy. Several robotic Embodied Energy systems, each representing a specific energy-storage and transduction methodology, are exemplified here. Although energy storage can take many forms in mechanical systems, we limit our depiction here to five of the most common types that can be harnessed by autonomous robots: electrical, mechanical, chemical, magnetic and thermal. Several of these categories overlap in conventional systems (for example, in electrochemical batteries or thermochemical heat storage), a property that can be exploited when merging different energy-storage and transduction technologies. Systems that store energy can vary wildly in their efficiency (Extended Data Table 1), material composition and even the states of matter they interface with (for example, solid state batteries, liquid redox flow batteries and gaseous hydrogen fuel cells). Similarly, the landscape of energy transduction mechanisms (for example, electromagnetic motors, combustion engines and hydraulic pistons) is vast, complicating design decision-making.

Fig. 2: Energy storage and transduction form the framework of the Embodied Energy design process.
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The Embodied Energy technologies shown are created by storing a specific type of energy in the structural or energy transduction components of a system. The images in the transduction pathway depict, from left to right, an electric comb drive, a bistable mechanical actuator, a soft combustion actuator, a magnetic solenoid actuator and a thermally responsive gel. The variable definitions are as follows: U, voltage; q, charge; H, magnetic field strength; B, magnetic flux density; V, volume; S0, standard entropy; T, temperature; C, specific heat capacity; m, mass; p, pressure; F, force; x, displacement; σ, mechanical stress; ε, strain. RFBs, redox flow batteries; SHES, sensible heat energy storage; SMES, superconducting magnetic energy storage.

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The intersection of energy storage and transduction will form the framework of our discussion, as Embodied Energy seeks to accomplish these tasks collectively. Generally speaking, Embodied Energy is best discussed in the context of robotics by examining its conversion to mechanical work (that is, actuation and locomotion). In the sections that follow, we will present existing technologies that can transduce different types of stored energy into mechanical actuation in robots. We will describe how these technologies can be implemented in multifunctional Embodied Energy systems, citing existing examples, and discuss future developments for each energy transduction category, concluding with an examination of nine Embodied Energy design principles.

Electrical to mechanical transduction

Untethered robots and their mechanical actuators are predominantly powered by rigid rechargeable batteries (for example, lithium-ion, lithium-polymer and nickel-metal hydride batteries). Some of the earliest notable cases of multifunctional energy storage involve structural power sources5,16,17, in which static, load-bearing components of machinery also supply electrical energy. A simple example is the use of lead-acid batteries in forklifts as the counterbalance for lifting heavy loads18. More sophisticated Embodied Energy examples include structural batteries in satellites19, spacecraft20 and electric vehicles4,21, lithium-polymer batteries that function as wings in unmanned aerial vehicles16, pliable, biomorphic zinc-air batteries that can serve as protective covers for robots22 and flexible galvanic thin-film batteries in flapping wing aerial vehicles23. In the latter example, the use of embodied electrical energy sources increased the operating time of a flapping wing aerial vehicle by 250% relative to designs using standard batteries and conventional wing materials.

The conversion of electrical energy to mechanical actuation is most commonly accomplished in robots by electric motors, although they do not store their own onboard energy. Electroactive polymers, so-called because they change size or shape in response to electric stimulus, are a class of materials that are capable of multifunctional energy storage. They have the capacity to quickly (t ≈ 10−3–10−4 s) undergo large reversible strains (εult > 300%)24,25 making them an attractive option for robots with muscle-like actuators24,25,26 and sensing capabilities27,28. Electroactive polymers can broadly be classified as either electronic (for example, electrostatic, electrostrictive and ferroelectric polymers) or ionic (for example, gels and ionic polymer-based composites) depending on their mode of action25.

Dielectric elastomer actuators (DEAs), a class of soft electrostatic transducers belonging to the electronic group, have been performing multifunctional electrical to mechanical energy conversion for decades29. During operation, DEAs store energy throughout their structure, with elastomer layers functioning as deformable capacitors. Consequently, DEAs can serve simultaneously as actuators, sensors and energy harvesters30. DEAs have been implemented in crawling31,32, gripping33, swimming34,35,36 and even flying robots37, while more recently introduced soft electrostatic transducers (for example, hydraulically amplified self-healing electrostatic (HASEL) actuators38,39) have combined solid and liquid dielectrics to produce additional functionalities, including hydraulic and pneumatic40 actuation modes. Unlike conventional electric motors, soft electrostatic transducers inherently store electrical energy and can assume ‘catch states’, in which negligible power is consumed while holding a position. When used in a multifunctional manner, soft electrostatic transducers provide a rich opportunity for Embodied Energy in robots, and have already been used for high-frequency, high-amplitude actuators39,41,42.

Ionic polymer–metal composites (IPMCs) have also been used in the creation of mobile robots43,44,45. Composed of a thin conductive polymeric material placed between two metal electrodes, IPMCs use the transport of ions into and out of the polymer for actuation. Although they generally produce lower actuation forces compared to soft electrostatic transducers, their ability to operate at low voltage (Vin ≈ 1–5 V versus Vin > 100 V for DEAs) and also generate a small voltage in response to deformation has made IPMCs both useful actuators and sensors in biomedical and engineering applications28,46,47,48.

We anticipate future improvements not just in the energy density of batteries, but also in the materials used in their composition14. Batteries with tuneable mechanical properties could serve a variety of functions outside of traditional energy storage, expanding the benefits of Embodied Energy to a wider array of robot designs. As exemplified in Fig. 2, a stretchable battery can theoretically be used as an extensible tendon in a walking robot or a wearable exosuit, thus combining electrical and elastic energy storage into a structural element that connects different system components. Fluidic energy storage using flow battery technologies is also a key innovation in this domain. For example, in 2019, a soft robotic fish was created with an embedded ‘electrolytic vascular system’1. This design was inspired by redox flow batteries and consisted of a distributed liquid electrolyte that also served as a hydraulic fluid. This multifunctional use of electrochemical energy storage enabled simultaneous power generation and fluidic actuation, which enabled the fish to swim for long durations (>36 h).

Mechanical to mechanical transduction

There are many methods for converting stored mechanical energy into motion, including springs, linkages, gear trains, cams and followers, and so on. However, multifunctional and embodied applications are far less common in modern machinery. One use case that has been explored is the inclusion of flywheels in spacecraft to both store energy and provide torque for attitude and control49,50,51.

For robots, one pathway towards improved mechanical energy management involves advancements in high-energy-density materials, composites and interfacial chemistry that can replace or supplement existing mechanisms. The field of soft robotics has provided such a platform for the latest innovations in Embodied Energy due to the vast design space offered by the high strain capabilities (εult > 1,000%), range of stiffnesses (E ≈ 1–105 kPa), and durability of soft matter, such as silicone elastomers, hydrogels and polyurethane rubbers52. Other characteristics of soft robots, including their ability to be fabricated by additive manufacturing methods (for example, three-dimensional (3D) printing and soft lithography)53, the existence of well-established actuation techniques (for example, fluidic, electrostatic)52,53,54, adaptability and human compatibility, all motivate synergistic applications for multifunctional and efficient power conversion technologies.

Soft robotics has historically embraced the storage or tuning of elastic energy in elastomeric structures for improved efficiencies and high-power actuation. Recent work has pushed this further by harnessing materials and geometric non-linearities to discretize the actuator response. Some non-linear soft actuators, for example, are characterized by instabilities that cause the actuator to undergo a snap-through response, in which a fast motion with a large stroke follows from a small external input. During the snapping phase, the elastic energy stored in the actuator structure is suddenly released and can be redirected towards the external world. This principle was recently exploited in the fabrication of bistable hybrid soft actuators inspired by the spinal flection of mammalian quadrupeds55. In another example, stored pressure-volume mechanical work was harnessed to create a jumping robot consisting of spherical caps that made use of a volumetric instability56. Embedded actuator sequencing has been achieved by connecting multiple non-linear balloon actuators, adding passive control to the energy conversion process8,57. We see this snap-through behaviour in nature as well; a classic example is that of the Venus flytrap58.

As robots continue to emulate biology and evolve towards hybrid hard–soft structures, there will be additional opportunities to generate unified musculoskeletal systems that provide energy storage, power and structural functionality. Series elastic actuators, in which a spring-like element is placed between an actuator and the end effector, are perhaps the simplest example of this concept. Figure 2 highlights how this approach to Embodied Energy can be used to improve the adaptability and durability of terrestrial robots. Integrating compliant elements such as series elastic actuators into robot architectures could lead to greater shock tolerance, more accurate and stable force control, lower reflected inertia and decrease inadvertent damage to the environment, all while storing energy59. Advancements in manufacturing techniques will also inform future designs for hybrid hard–soft robots that can structurally store mechanical energy. Multimaterial additive manufacturing represents a clear step towards this approach. An idealized process would be able to dynamically tune the chemical and mechanical properties of a part during synthesis to produce functionally graded composites and monolithic robots. Just as humans capture and reuse elastic energy with their muscles and tendons, we also expect future robots to more commonly harvest, store and reuse energy from inertial forces60.

Chemical to mechanical transduction

Humans and other animals rely on chemical fuels such as glucose and fat to serve as their primary energy source for mechanical work. Similarly, combustion engines convert energy-dense hydrocarbons into power for transportation, but the high temperatures required necessitate the use of rigid and dense metal bodies (or frameworks) in most applications. Compressed, gaseous hydrocarbon fuels have now been used for both variable compliance61 and, when combusted, high-power-density actuation in soft elastomeric robots2. Although the efficiency is not yet high, the large energy density of these hydrocarbon fuels, along with their multifunctional capabilities, can increase the high power performance and adaptability of these robots compared to inert gases61,62. More recently, liquid fuels have been implemented in multifunctional power–structure–actuation systems to achieve cyclic movement in untethered robots63. The ‘octobot’, unveiled in 2016, used a distributed chemical energy system (platinum-catalysed H2O2 decomposition) coupled with a microfluidic logic circuit to autonomously achieve mechanical actuation of the tentacles of a 3D printed octopus3.

We anticipate further advances by storing convertible fuel sources within intelligent structural and machine elements. Autophagous systems are one such approach, wherein physical loads are borne by structural components that also provide energy in a ‘self-consuming’ process. Previous work in this area has been explored for use in aerospace applications5,9. The structural requirements for launching vehicles into space greatly exceed those needed for normal operation; with the components consequently sized for launch, the lifetime and efficiency of these vehicles would increase by breaking down and harvesting energy from their excess materials. This same strategy could be implemented in robots, and is supported by research involving autophagous metal–air batteries64, structural beams pressurized with gaseous fuels9 and thermoplastic matrix composites that can be converted to fuel and burned with liquid oxidizers65.

Naturally, end-use applications must be carefully considered when designing autophagous structure–power systems. The large energy density of solid fuels comes at the expense of ease-of-servicing and long-term durability as the structure is depleted. Recyclable, biodegradable and single-use devices do show promise in applications including surveillance, exploration and medicine, but more traditional robots will need to prioritize refuelling capabilities, possibly through the use of modular designs, energy harvesting, and secondary or emergency means of power generation to ensure perpetual functionality. One difficult challenge that can be envisioned is the non-homogeneous consumption of materials in autophagous systems. Using the autophagous metal–air battery as an example, a localized catastrophic failure could incapacitate the system, leaving a fraction of the remaining energy inaccessible. A solution to this problem is the use of materials and configurations that leave behind residual structures that can still function in their intended roles. Bimetallic shells could be used in configurations in which only one of the two compounds is consumed. Porous structures containing internalized liquid or adsorbed gaseous fuels are another promising solution, as shown in Fig. 2. A recent report described an ultraporous (7,310 m2 g−1) metal–organic framework that can store large volumes of methane and hydrogen gases that could be used to power vehicles, aircraft and even robots66.

Magnetic to mechanical transduction

The coupling of electricity and magnetism leads to a fair degree of overlap when discussing magnetic energy-storage applications. Energy can be stored in the magnetic field of an inductor or a superconducting coil (a process called superconducting magnetic energy storage), for example, but current flow is required. Many robotic components and actuators, including motors, valves, pumps, solenoids, switches and relays, all take advantage of this same basic electromagnetic principle: a conducting coil produces a magnetic field when energized by an electric current, which in turn induces movement in a magnetic body.

Many improvements to magnetic actuators have been realized over the past few decades, most recently with regard to smaller size scales and the adoption of different substrate materials67,68,69,70. Magnetic microrobots, in which the body and magnet are mostly one and the same, represent an exciting new set of capabilities, especially in the biomedical or in vivo realms71,72,73. Constructing the robot from magnetic materials enables the transduction of magnetic energy into mechanical motion to be embodied at the structural level. Although remote power generation eliminates the need for an integrated energy-storage system, external control by bulky, stationary magnetic coils restricts the scope of these robots to some degree.

Although examples are limited, magnetic actuation presents an excellent opportunity for Embodied Energy technologies, as the coil and magnet configurations used for actuation can also be used for energy harvesting (a magnet travelling through a coil will induce an electromotive force, whereas electrically powered actuators can in turn move magnetic elements). One example is the use of electromagnetic dampers60,74 within end effectors for proprioceptive force control, energy generation and locomotion, as demonstrated in Fig. 2. Another example is the ‘Moball’ robot, which contains moveable, permanent magnets that can provide steering and enable rolling movements by changing the device’s centre of mass, in addition to generating energy by passively oscillating within solenoids75. Magnetic actuator technologies are also being expanded to non-rigid materials; stretchable inductors for compliant power electronics76,77 are one interesting emerging application.

Improvements in offboard magnetic control will be required for future robots to maximize the potential of Embodied Energy in this domain. We can also envision coupling magnetic actuation and energy harvesting or delivery with the existing electrical systems in larger robots to achieve higher efficiencies and a wider range of functionalities.

Thermal to mechanical transduction

Thermal to mechanical energy conversion is commonly accomplished by combustion engines, which are ubiquitous in modern machinery. However, the mechanical complexity, weight, size and scaling limitations of heat engines complicate integration into other energy–power systems and typically restrict them to larger applications in industry and transportation. Heat engines make up for their lower efficiencies (efficiency η ≈ 25–40%)78 relative to other energy transducers by consuming high-energy-density reactants. One established technique for improving the efficiency and expanding the utility of combustion engines is the capture and reuse of waste heat (for example, through the use of exhaust gas heat recovery, organic Rankine cycle units or thermoelectric devices)78,79. Another approach is to use an alternative fuel source shared by another onboard, power-generating device. Hybrid electric vehicles represent a simple example in which an electric and thermal system can operate synergistically through the addition of an optimizing control element. A related technology is 'combined heat and power', wherein fuel is used in the concurrent production of electricity and thermal energy, the latter of which is efficiency captured and used in processes such as heating and cooling. The energy systems of future robots could all stand to benefit through the incorporation of similar processes.

At smaller size scales, bimetallic strips are among the simplest technologies used for thermal actuation. Heating a pair of thin, bonded metal parts with different coefficients of thermal expansion will cause the strip to bend. Recently, this technique of coupling materials with different thermal properties has been extended to soft matter to create fibre-based, muscle-like actuators capable of producing large stroke cycles and withstanding high strain (in some cases >1,000%)80,81.

Thermophoresis, a phenomenon in which temperature gradients cause particles to experience a net force that may induce flow, represents another instance of thermal to mechanical energy transduction. Over the past few decades there has been growing interest in using thermal gradients to manipulate and propel micro- and/or nano-scale objects. Recent achievements in the medical field include the creation of thermophoretic nanomotors that can target and penetrate cancer cells82, and the development of a microrocket robot that can be optically actuated through a bloodstream83.

Shape memory polymers (SMPs) are another promising class of materials and actuators that can be engineered to react to both thermal and magnetic stimuli. As their name suggests, SMPs are capable of undergoing a shape transformation—the entropy-driven restoration of a previous mechanical deformation—that is fast, reversible (trecovery < 1 s to minutes), and reprogrammable84. The favourable mechanical properties of SMPs, including high ultimate strains (εult < 800%), tuneable stiffnesses (E = 10−4–3 GPa) and a wide range of transition temperatures (Tcrit = −10 to 100 °C)85 have seen them used in medical devices86,87, fabrics and wearables88, sensors89, robots90,91 and aerospace technologies92. Additionally, the multifunctionality associated with storing several different shape configurations within a single or composite material84,93,94, which can serve as both a structure and an actuator91, makes SMPs an attractive option for Embodied Energy technologies. Shape memory alloys (SMAs) comprise a similar group of smart materials that can return to their original forms when subjected to changes in temperature or magnetic field strength. SMAs are typically stiffer than SMPs (E ≈ 28–83 GPa, with generally similar moments of inertia)85 and although they possess limited strain capabilities (εult < 8%)95 their high power densities (Γ = 103–105 kW m−3)54 have contributed to their use in a wide array of robots and actuators95,96,97,98,99,100.

With waste heat being a substantial by-product of many mechanical systems, it is easy to visualize how SMAs and SMPs could be integrated and embodied within existing machine architectures to improve energy efficiency, weight or device performance. Both materials, for example, could be used as structural or skin-like elements that actuate to enable thermoregulation in different machines. Shape memory actuators could also be configured to respond to the waste heat of solar energy harvesters or heat engines, or used together with thermoelectric or pyroelectric devices101,102 (Fig. 2). A recent report detailed the creation of an insect-scale, autonomous crawling robot containing a platinum-coated SMA artificial muscle that was powered by catalytic combustion with an onboard methanol fuel supply103. Another publication demonstrated how low-grade waste thermal energy could be converted into electrical energy through the use of artificial polymer muscles104. More than 120 W of electrical energy per kilogram of muscle were successfully produced, which could be used in powering autonomous sensors.

Embodied Energy design principles

Creating robots that effectively embody energy can be accomplished by optimizing for endurance and operating time, while overcoming key design contradictions (for example, increasing the energy content of a robot while maintaining its volume.). To that end, we have identified several key design principles that can be applied during robot development and production. Figure 2 depicts how these design principles can be used in both existing and hypothetical Embodied Energy technologies.

First, design the technology with size, weight and power trade-offs in mind. Whereas power density is inversely proportional to weight and volume, operating time scales proportionally with size in untethered robots. Using embedded, energy-dense fuels is one approach to optimizing for high power at smaller sizes. The prospect of integrated versus modular assembly represents another aspect of this trade-off. Modular designs can be easier to assemble, service and reuse. A complex and heavily integrated design can probably achieve higher performance and should execute an array of self-sustaining functions, at the cost of simplicity in maintenance.

Second, integrate energy storage into structural elements. Using batteries as structural elements can eliminate the need for certain load-bearing components. Mass or volume elements that would normally bear loads can be reassigned to perform functions unrelated to energy storage.

Third, make a system serve itself by performing auxiliary helpful functions. Synergistic systems can improve machine autonomy while limiting the need for human intervention. Halogen lamps represent a simple example—they regenerate their own filament when in use through the redeposition of evaporated metal105. Similarly, in the redox flow battery-inspired electrolytic vascular system1 the same liquid used for hydraulic actuation is also used for energy storage, and the pumping of this liquid recirculates the soluble ions to improve the rate of charge transfer.

Fourth, use hybrid hard–soft structures to create adaptable designs. Using compliant, muscle-like materials can lead to durable robots that can dampen or even absorb and redistribute forces, traverse difficult terrains and operate with many degrees of freedom.

Fifth, use composite or porous materials to store energy. Composites can contain both structural and energy-storing domains. Similarly, porous materials, as in the example of gas adsorbent metal lattices66, can form lightweight structures that house fuel or energy in their pores.

Sixth, harvest energy from the environment. To achieve fully autonomous robots, we must equip them with the technology to extract energy from their surroundings. Motion-driven microgenerators and photovoltaic cells are among the most mature energy-harvesting technologies106, although efficiency and power-density limitations exist.

Seventh, reuse waste energy. Recovered energy can be reconverted into onboard power, as in exhaust gas heat recovery systems, or repurposed for a secondary function, such as heating and cooling in 'combined heat and power' systems.

Eighth, take advantage of resonance. Robot efficiency and longevity can be increased by driving systems with parameters that lead to high-amplitude outputs. Furthermore, operating actuators at resonance will require less energy input (for example, a pneumatically powered actuator may need to be inflated fewer times and endure less stress for an equivalent distance traversed).

Ninth, compensate for weight through interaction with the environment. Machine morphology should be adapted to derive advantages from their surroundings. Hydrofoils are used to lift ships out of the water to reduce drag, and vortex strips are implemented in aircraft wing designs to improve lift105. In nature, many aquatic animals achieve buoyancy due to their energy-storing fat reserves.

Challenges and future advancements

A universal methodology for characterizing and evaluating Embodied Energy systems in a design context has yet to be established. However, techniques for characterizing the advantages of multifunctional systems, in general, have been proposed. Johannisson et al.107 introduced a ‘residual performance methodology’, that involves comparing the specific properties (for example, mass, shear strength and specific energy) of a multifunctional block with those of two or more monofunctional systems (for example, structure and energy storage). Other approaches include establishing a multifunctional efficiency metric or directly calculating the change in a value of interest as a function of different design variables. Thomas et al.9 demonstrated this by modelling the flight endurance time of a hypothetical, electrically powered unmanned aerial vehicle in terms of the relative masses of the onboard batteries, solar cells and structure to draw conclusions about the most effective multifunctional configurations.

To envision the potential efficacy of integrated energy-storage and transduction systems, we developed a multifunctional version of the classic Ragone plot108, as shown in Fig. 3. This graph predicts the range of energy- and power-density values attainable by a theoretical, merged energy-storage and actuator system, based on the energy density, power density and efficiency of the component parts4,16,54,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131 (see Fig. 3 legend for details). It is intended as a tool for exploring different robot designs when energy and power requirements are known.

Fig. 3: Multifunctional Ragone plot of Embodied Energy storage and energy transducer combinations.
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Each pair of intersecting line segments (corresponding to a specific number and colour) represents the range of predicted energy-density and power-density values for a given energy storage and actuator combination, based on existing products and prototype devices4,16,54,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131. Predicted energy density is the product of an energy source’s energy density Z, efficiency α and the efficiency η of the energy transducer in which it is embodied. Predicted power density is the product of an energy transducer’s power density Γ, efficiency η and the efficiency α of the energy-storage system in which it is embodied. The intersection points of the line segment pairs are arbitrarily chosen for visibility.

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The pairs shown in Fig. 3 were selected based on complementary features or their use in previously reported prototypes (see Extended Data Table 1 for plotted values and their corresponding references). The energy sources in these hypothetical combinations can be thought of as being fully embodied within their assigned energy transducer, in which they will serve multiple functions. Combinations 1–6, for example, can be thought of as structural battery configurations used together with different electromechanical actuators. Combination 13 implies an engine or turbine configuration that takes energy from the burning of its hydrocarbon support structure, rather than a traditional fuel reservoir that serves a single energy-storage function.

Although the full scope of possible systems and combinations is impossible to sample, these data do enable a rough comparison of the energy content and output of different hypothetical Embodied Energy arrangements. For example, combinations 10, 11 and 13 store energy as a hydrocarbon fuel and are akin to autophagous power systems; however, despite possessing much greater energy densities than many of the other systems, the upper bound of their power-density range is not substantially different from several battery- and motor-driven designs due to the low efficiencies involved. The graph does not take into account mass budgets and efficiency penalties of supplementary systems that may be necessary for the construction or operation of these hypothetical systems. Similarly, this plot does not capture the additional functionalities or non-energy-storage characteristics that may be beneficial in certain designs (for example, material compatibility, scalability or cost). All Embodied Energy technologies, along with their inherent characteristics and design trade-offs, must necessarily be evaluated in the context of their intended environment and applications.

Embodied Energy both presents and promises to solve future challenges. Size, weight and power trade-offs, for example, will always present difficulties to robotics researchers, particularly as smaller robots and personal devices, each possessing considerable payload restrictions and energy requirements, are pursued. Microrobots present an extreme case, with many of the latest innovative designs requiring an electric tether to deliver power132. Several are limited to specialized environments132, and most also forgo conventional actuators (that is, d.c. motors) due to fabrication limitations and the unfavourable scaling of friction and electromagnetic forces133. If the advantages promised by microrobot technologies (for example, swarm capabilities, exploration, search and rescue, and medical intervention) are to be realized, multifunctional design strategies using Embodied Energy must be pursued.

Other challenges must be overcome as well, including the need for new, compatible materials that operate synergistically with existing technologies, and yet unimagined ones. Examples include conductive and corrosion-resistant materials that could function as battery electrodes and ion exchange membranes, energy-dense solid polymer fuels for autophagous systems, controllable shape-morphing materials134 and biocompatible materials that can be assembled into lightweight composites composed of organic, inorganic and even living matter. Advancements in additive fabrication techniques across multiple scales, coupled with predictive (inverse) design will be necessary to increase both the compositional and structural complexity of robots, and to realize new levels of multifunctionality.

The tighter integration of sensing, actuation, control and power towards biological size scales (that is, organs and tissue) will realize first-order improvements in robot autonomy. Whereas synthetic systems are striving to achieve tissue-level autonomy, biohybrid ones already do. Consequently, we expect research in this area to be fervently pursued in the immediate future. 3D printing will also be an increasingly used tool; direct ink writing135, polyjet136 and digital light processing137,138 have all been used to create complex robots with intricate internal networks out of soft materials. The use of new, more energy dense materials will also provide new design tools for directly printing robots. Finally, the direct chemical to mechanical conversion of energy, as demonstrated with hydrocarbon fuels, will probably become increasingly used to provide the greater energy densities and efficiencies required for biological magnitudes of endurance and adaptability.

Finally, the multifunctional energy-storage paradigm we are attempting to codify can be further separated into passive and active control. Within these logic mechanisms there is further opportunity for multifunctionality; the structures themselves provide control (for example, origami139, bistable beams140,141 and elastomeric actuators142,143,144,145). In this context, information processing becomes another material property embodied in the physics of the soft, architected structure, enabling local computations that seamlessly integrate the sense–decide–response chain146,147. For example, networks of elastomeric light guides have demonstrated the information density and sufficient sampling rates to classify deformation states through offboard neural network training148. Notably, the mechanical non-linearity of elastomeric materials is even capable of embodying recurrent neural network behaviour, as demonstrated in the dynamics of a silicone octopus arm149. Embedded computation has the added benefit of requiring less energy, as the information processing is inherently coupled to, or a by-product of, the deformation and environmental loading. Embodied Energy and Embedded Computation, therefore, will be intricately linked in the future of advanced robotics research.

The conjoined aspects of harvesting, storing, transforming and releasing energy provide a unique lens through which to view the evolution of autonomy and intelligence. Such considerations similarly challenge roboticists to rethink how to design, program and deploy their creations into the world. The design principles that result from the proposed Embodied Energy paradigm have the potential to yield new multifunctional energy-storage systems that improve the multi-objective optimization of robot endurance and adaptability. The frontier of this research lies in integrating advancements in predictive multiscale design, multifunctional materials, digital manufacturing and robotics.