The Soft Robotics Revolution: Engineering Compliance for a Human-Centric and Unstructured World

Executive Summary

Soft robotics represents a fundamental paradigm shift in engineering, moving away from the rigid, high-precision systems that have long dominated industrial automation toward compliant, adaptable machines inspired by biological organisms. Constructed from materials with mechanical properties similar to living tissue, such as silicone elastomers, hydrogels, and shape-memory polymers, soft robots prioritize safety, adaptability, and resilience over the speed and absolute accuracy of their rigid counterparts. This report provides a comprehensive analysis of the field, examining the core principles that differentiate it from conventional robotics, the material science and fabrication techniques that enable it, the diverse actuation and control strategies used to animate it, and its transformative applications.

The central value proposition of soft robotics lies in its ability to safely interact with humans and navigate complex, unstructured environments. In healthcare, this translates to less invasive surgical tools, personalized rehabilitation exoskeletons, and biocompatible implantable devices that can actively modulate biological responses. In manufacturing, soft grippers are revolutionizing the handling of delicate and irregularly shaped objects, enabling safer and more versatile human-robot collaboration. For exploration and rescue, the deformability of soft robots allows them to traverse cluttered and confined spaces—from the rubble of a collapsed building to delicate marine ecosystems—that are inaccessible to rigid machines.

However, the field faces significant technical hurdles. The very compliance that provides these advantages also introduces profound challenges in durability, power autonomy, sensor integration, and, most critically, precise control. Modeling and managing systems with theoretically infinite degrees of freedom and non-linear material behaviors requires a departure from traditional control theory, pushing the field toward data-driven approaches like machine learning.

The strategic outlook for soft robotics is one of convergence. Future advancements will likely depend on hybrid systems that strategically combine soft and rigid components, the development of more robust and efficient smart materials, the creation of untethered power sources, and the fusion of “embodied intelligence” from the robot’s physical form with the adaptive learning of artificial intelligence. By addressing these challenges, soft robotics is poised to extend the reach of automation into nearly every aspect of society, from personal healthcare and assistive living to environmental stewardship and space exploration, heralding an era of machines that are not only more capable but also fundamentally more compatible with the natural world and human life.

A New Paradigm in Robotics: From Rigid Links to Compliant Continuums

The emergence of soft robotics marks not merely an evolution in material selection but a revolutionary departure in the philosophy of robot design, control, and interaction. For decades, the field of robotics has been defined by rigid links, discrete joints, and deterministic control systems engineered to impose precision and order upon structured environments. Soft robotics challenges this orthodoxy by embracing compliance, continuous deformation, and bio-inspired adaptability. This section establishes the foundational principles of this new paradigm, contrasting its core tenets with those of conventional robotics and introducing the concept of embodied intelligence, where a robot’s physical form becomes an integral part of its computational process.

Redefining the Robot: Core Principles of Compliance and Adaptability

At its core, soft robotics is the science and engineering of robots constructed primarily from materials with elastic moduli comparable to those of soft biological tissues, typically in the range of to Pascals.1 This class of materials includes elastomers like silicone rubber, as well as hydrogels, fluids, and various polymers, standing in stark contrast to the metals, ceramics, and hard plastics (with moduli greater than GPa) that form the bodies of conventional robots.1

The defining characteristic that arises from this material choice is compliance—the intrinsic ability of the robot’s body to deform elastically under applied forces.3 This property is central to the soft robotics paradigm for several key reasons. Firstly, compliance enables inherently safer physical interactions. When a soft robot collides with an object or a person, it deforms to absorb and distribute the impact energy over a larger surface area, significantly reducing the peak contact pressure and minimizing the risk of damage or injury.1 This mechanical compliance is a built-in safety feature, unlike the software-based safety protocols and external sensors required to make rigid robots safe for human proximity.5

Secondly, compliance facilitates adaptation to uncertain and unstructured environments. A soft robotic gripper, for instance, can passively conform to the shape of a delicate, irregularly shaped object like a piece of fruit, achieving a stable grasp without requiring a precise model of the object’s geometry or complex sensor feedback.7 This adaptability stems from the robot’s physical properties rather than its computational prowess.

This shift in material philosophy leads to a radical change in morphology. Instead of being assembled from discrete rigid links and a finite number of actuated joints, many soft robots are designed as continuum bodies.1 These monolithic structures possess a theoretically infinite number of degrees of freedom (DoF), allowing them to generate complex, fluid motions such as high-curvature bending, twisting, and stretching.3 This capability, inspired by biological systems like octopus tentacles, elephant trunks, and tongues, enables soft robots to maneuver through confined spaces and manipulate objects in ways that are fundamentally impossible for their rigid-bodied counterparts.1

The Contrast with Conventional Robotics: Precision vs. Adaptability

The divergence between soft and conventional robotics can be understood as a fundamental trade-off between precision and adaptability. Conventional rigid robots are masterpieces of determinism, optimized for high precision, absolute repeatability, immense strength, and high-speed operation within meticulously structured and predictable environments, such as the automotive assembly line.7 Their design, based on well-understood kinematics and dynamics, allows for precise mathematical modeling and control, enabling them to execute pre-programmed tasks with sub-millimeter accuracy.

Soft robotics, in contrast, relinquishes the pursuit of absolute precision in favor of flexibility, resilience, and adaptive interaction.6 This makes them uniquely suited for the dynamic, unpredictable, and often delicate contexts of human-inhabited spaces, natural environments, and the human body itself.3 The inherent strengths of one paradigm are the inherent weaknesses of the other. The finite DoF of rigid robots, which makes them controllable and predictable, also limits their mobility and dexterity, and their high stiffness makes them a potential hazard to delicate objects or humans.12 Conversely, the very properties that make soft robots safe and adaptable—their continuous deformability and non-linear material behavior—make them exceptionally difficult to model accurately, challenging to control with high precision, and generally unsuitable for tasks requiring high force or the manipulation of heavy payloads.6 This dichotomy establishes two distinct but complementary domains for robotic applications, with rigid systems excelling at tasks of imposition and soft systems excelling at tasks of interaction.

Feature	Rigid Robotics	Soft Robotics
Core Materials	Metals, hard plastics, ceramics	Silicone elastomers, hydrogels, fluids, soft polymers
Elastic Modulus	GPa	Pa
Primary Goal	Precision, speed, strength, repeatability	Adaptability, safety, compliance, resilience
Degrees of Freedom	Finite, defined by discrete joints	Continuous, theoretically infinite
Control Philosophy	Position control, deterministic, model-based	Morphological computation, data-driven, learning-based
Approach to Environment	Avoids contact; operates in structured spaces	Embraces contact; operates in unstructured spaces
Definition of “End-Effector”	Clearly defined tool point (e.g., gripper tip)	Ambiguous; can involve the entire body (e.g., whole-body grasping)
Key Strengths	High accuracy, high payload, high speed	Safe interaction, adaptability, maneuverability in confined spaces
Key Weaknesses	Unsafe for direct human contact, limited mobility, poor in unstructured environments	Low precision, low payload, difficult to model and control
Typical Applications	Industrial automation, welding, pick-and-place	Healthcare, human-robot collaboration, search and rescue, delicate object handling

Embodied Intelligence: How Material and Morphology Shape Behavior

Perhaps the most profound conceptual shift introduced by soft robotics is the principle of embodied intelligence, which is often realized through morphological computation.1 This concept posits that a significant portion of what is traditionally considered “computation”—processing information to make decisions—can be offloaded from a centralized, electronic brain (the controller) to the physical body of the robot itself.3 The robot’s material properties, its physical shape (morphology), and its dynamic interaction with the environment collectively perform computational tasks, simplifying the demands on the explicit control system.1

A clear example is the passive adaptation of a soft gripper. A rigid gripper requires a sophisticated vision system to identify an object, a processor to calculate its shape and orientation, and a control algorithm to command the precise trajectory and force for each finger to achieve a stable grasp. A soft gripper achieves the same outcome by simply closing around the object; its inherent compliance causes it to automatically conform to the object’s shape, distributing forces evenly without complex sensing or calculation.3 In this act, the physical properties of the gripper have “computed” the optimal shape for grasping. This represents a fundamental blurring of the line between the robot’s body and its brain.3

This principle reveals a deeper distinction between the two robotic paradigms. Rigid robotics operates under a philosophy of environmental control, where the primary goal is to minimize physical interaction to maintain a precisely controlled state, often by isolating the robot from its surroundings.3 Contact with the environment is typically treated as a disturbance or an error to be corrected. Soft robotics, by its very nature, operates under a philosophy of environmental exploitation. It is designed to embrace and leverage physical contact. The interaction is not a bug but a feature, a necessary part of the system’s operation that provides information and simplifies control. The robot’s body is designed to harness the physics of its environment to achieve its goals, turning the world from an obstacle to be avoided into a partner in computation.

This re-evaluation of physical interaction extends to the very definition of mechanical failure. In traditional rigid-body engineering, phenomena like buckling are considered catastrophic failure modes to be designed against at all costs.16 In soft robotics, however, where large, reversible deformation is the norm, such behaviors can be repurposed as functional mechanisms. Researchers have demonstrated, for example, that the controlled, reversible buckling of elastomeric structures can be used to generate rotary motion, transforming a classical failure mode into a novel method of actuation.16 This illustrates that the design of soft robots requires a fundamental rethinking of classical mechanical principles, where the entire spectrum of material behavior, including non-linearities and instabilities, becomes a part of the functional design toolkit.

The Material Foundation of Soft Robotics

The unique capabilities of soft robots are born from the materials of which they are made. The selection of a specific polymer, gel, or composite is not merely a structural choice but a decision that defines the robot’s potential for movement, its mode of actuation, its capacity for sensing, and its overall behavior. This section provides a detailed examination of the key material classes that form the foundation of soft robotics, analyzing their chemical and physical properties, their specialized fabrication methods, and the critical performance trade-offs that guide their application. The evolution from simple molding of passive elastomers to the additive manufacturing of multi-functional, “smart” materials is a central theme, as the fabrication method itself is a key enabler of functional integration and complexity.

Elastomers: The Workhorse of Soft Actuation

Elastomers, particularly silicone rubbers, are the most prevalent materials in soft robotics due to their exceptional combination of flexibility, resilience, and ease of processing. They form the primary structure for the majority of fluidically actuated soft robots.

Silicone Rubbers: Properties, Chemistries, and Performance Trade-offs

Silicone elastomers are prized for a suite of advantageous properties. They exhibit extreme elasticity, capable of stretching to over 600% of their original shape without permanent deformation, and possess a low elastic modulus, giving them a softness comparable to human tissue.17 This inherent compliance is quantified by their durometer hardness on the Shore scale, with materials used in soft robotics typically ranging from the very soft Shore 00-30 to the firmer Shore 30A. Furthermore, silicones offer excellent thermal stability, resistance to environmental degradation, and, crucially for medical applications, biocompatibility.18

The performance of a silicone component is heavily influenced by its curing chemistry, with two primary types dominating the field:

Platinum-Cure Silicones: These systems use a platinum-based catalyst to initiate the cross-linking process. They are favored for high-performance applications due to their superior mechanical properties, long-term stability (uncured shelf-life), and negligible shrinkage upon curing.17 Their biocompatibility makes them suitable for skin-safe and food-safe applications. Popular formulations in research include the Dragon Skin series and Plat-Sil Gel 25.19 Their main drawback is a sensitivity to certain chemicals (like sulfur, tin, and some amines) that can inhibit the curing process, requiring careful handling and mold preparation.17
Tin-Cure (Condensation-Cure) Silicones: These offer a more cost-effective alternative and are less susceptible to cure inhibition.17 However, this comes at the cost of inferior mechanical properties and a notable shrinkage of approximately 1% during curing, which must be factored into the design of precision components.17 They also have a shorter library life, as they can become brittle over time.

A significant challenge common to all silicones is their poor adhesion. They are notoriously difficult to bond to other materials—or even to themselves once fully cured—using conventional adhesives like epoxies or cyanoacrylates.17 This necessitates design strategies that rely on mechanical interlocking (e.g., undercuts and overhangs) or specialized surface treatments like plasma activation to achieve robust bonds.17

Fabrication Focus: From Molding and Casting to Additive Manufacturing

Given that the high compliance of elastomers makes traditional subtractive manufacturing (machining) impractical, molding and casting has long been the primary fabrication method. This multi-step process involves:

Mold Creation: The mold, which defines the negative space of the final part, is typically created using 3D printing or CNC machining for repeatability.
Silicone Preparation: The two parts of the liquid silicone (e.g., Part A and Part B for a platinum-cure system) are precisely measured and thoroughly mixed.17
Degassing: The mixed liquid silicone is placed in a vacuum chamber to remove trapped air bubbles. This step is critical, as bubbles create weak points that can lead to catastrophic failure, such as ruptures in the thin walls of pneumatic actuators under pressure.17
Casting: The degassed silicone is poured or injected into the prepared mold.
Curing and Demolding: The silicone is allowed to cure (harden) for a specified time, after which the finished part is removed from the mold.17

While effective, this process can be labor-intensive and limits geometric complexity. The advent of additive manufacturing (3D printing) is revolutionizing soft robot fabrication. Techniques like Direct Ink Writing (DIW), also known as robocasting, allow for the layer-by-layer deposition of specialized silicone inks.4 This approach is not merely a faster way to prototype; it is a transformative technology that enables the creation of monolithic, functionally integrated robots.1 With multi-material 3D printing, it is possible to seamlessly combine materials with different properties—for example, embedding conductive pathways for sensing directly within a soft actuator body, or locally varying the stiffness of a structure to program its deformation.4 This ability to integrate sensing, actuation, and structure into a single, continuous body fulfills one of the core philosophical goals of soft robotics and is a key enabler of future complexity.1

Hydrogels: Biomimetic Materials for Medical and Aqueous Applications

Hydrogels represent a class of materials that pushes soft robotics even closer to biology. Their unique properties make them a compelling choice for applications requiring direct interaction with biological systems.

Properties and Stimuli-Responsive Behavior

Hydrogels are three-dimensional networks of hydrophilic polymer chains capable of absorbing and retaining enormous quantities of water—often exceeding 90% of their total mass.18 This high water content gives them an exceptional softness and compliance that closely mimics that of biological tissues, along with excellent biocompatibility.22

The most significant feature of “smart” hydrogels is their stimuli-responsive nature. The polymer network can be designed to undergo significant volume changes—swelling or shrinking—in response to specific environmental triggers. These stimuli can include changes in temperature, pH, light intensity, or the presence of electric or magnetic fields.23 This property allows the hydrogel itself to function as an actuator, converting a chemical or physical signal directly into mechanical work. This makes them highly promising for applications such as environmentally sensitive robotic skins, targeted drug delivery systems that release their payload in response to local biological cues, and artificial muscles.24

Overcoming Inherent Limitations: Mechanical Strength and Stability

Despite their biomimetic appeal, hydrogels suffer from several critical limitations that have hindered their widespread use in robotics. They typically exhibit very poor mechanical strength and are prone to tearing or damage under load.26 Their response time to stimuli can be slow, often limited by the diffusion of ions or water.23 Furthermore, because they are water-based, they are susceptible to dehydration and loss of function when operated in open-air environments.26

Significant research efforts are focused on overcoming these weaknesses. Mechanical strength can be improved by engineering more robust network structures, such as interpenetrating double networks, or by incorporating reinforcing nanomaterials like graphene or silica nanoparticles into the hydrogel matrix.23 The problem of dehydration is being addressed by developing hybrid organo-hydrogels, adding salts that lower the vapor pressure of the internal water, or encapsulating the hydrogel within a thin, flexible, and impermeable elastomeric skin.23

Shape-Memory Polymers (SMPs): Programming Form and Function

Shape-memory polymers introduce the concept of programmability directly into the material itself, enabling the creation of structures that can transform their shape on command.

The Shape-Memory Effect: Mechanisms and Triggers

SMPs are a class of “smart” materials that can be deformed from an original, permanent shape into a stable, temporary shape. They will hold this temporary shape indefinitely until exposed to a specific external stimulus, which triggers the material to recover its original, permanent form.4

This behavior is governed by the polymer’s molecular architecture, which consists of two main components: fixed cross-links that define the permanent shape, and reversible switching segments that “freeze” the temporary shape in place.29 The most common mechanism is thermally induced. The material is heated above a characteristic transition temperature (), which can be either its glass transition temperature () or melting temperature (). Above this temperature, the switching segments become mobile, allowing the material to be easily deformed. It is then cooled below while held in the deformed shape, locking the switching segments and fixing the temporary form. Subsequent reheating above releases the stored strain energy, causing the material to autonomously return to its permanent shape.28 While heat is the most common trigger, SMPs have also been developed that respond to light, electricity, moisture, or specific chemical environments.4 Some advanced SMPs can even be programmed with multiple temporary shapes (triple- or multiple-SME) or exhibit a reversible two-way shape-memory effect (2W-SME).29

Applications in Deployable Structures and Reconfigurable Robotics

The ability to program and trigger shape change makes SMPs exceptionally well-suited for creating untethered, self-actuating soft robots.27 This is particularly valuable for applications where external power and control lines are impractical. For example, a robot could be compactly stored in a temporary shape and then “self-deploy” into its functional form upon activation, a concept with significant potential for space applications, medical stents, or self-assembling structures.29 The advent of 4D printing, which combines 3D printing with time-responsive materials like SMPs, allows for the fabrication of components that are pre-programmed to transform their shape or function over time after they are printed.30

Emerging Smart Materials and Composites

Beyond these primary categories, a diverse and growing palette of advanced materials is expanding the capabilities of soft robotics.

Electroactive Polymers (EAPs): These materials actuate directly in response to an electric field. Dielectric Elastomers (DEs), for example, consist of a soft insulating membrane sandwiched between two compliant electrodes; when a high voltage is applied, the electrostatic pressure squeezes the membrane, causing it to expand in area.18 They offer high energy density and fast response but typically require very high operating voltages. Ionic Polymer-Metal Composites (IPMCs) are another type that bend in response to a low voltage due to the migration of ions within the polymer matrix.23
Liquid Crystal Elastomers (LCEs): These materials combine the rubbery elasticity of an elastomer with the orientational order of liquid crystals. This internal structure allows them to undergo large, programmable, and anisotropic shape changes in response to stimuli like heat or light, enabling complex movements.18
Fiber-Reinforced Composites: By strategically embedding inextensible fibers within a soft elastomeric matrix, designers can precisely control the anisotropic behavior of an actuator. When a pneumatic actuator with embedded fibers is inflated, the constrained expansion forces it to bend, twist, or extend in a predetermined manner, transforming simple pressure into complex motion.18

The choice among these materials reveals a fundamental design trade-off that exists at the heart of soft robotics. On one end of the spectrum are “passive” or “dumb” materials like basic silicone elastomers. They are robust, powerful, and fast when paired with external fluidic systems, but this performance comes at the cost of tethering and reliance on a complex external “brain” of pumps and valves.7 On the other end are “active” or “smart” materials like SMPs and stimuli-responsive hydrogels. The actuation logic is embedded directly within their molecular structure, enabling untethered autonomy with simple external triggers.27 However, this embodied intelligence is typically paid for with significantly lower performance in terms of speed, force, and durability.4 The challenge for the soft roboticist, therefore, is to navigate this spectrum, deciding where to locate the system’s intelligence—in the external controller or within the material itself—to best suit the demands of a given application.

Material Class	Specific Examples	Key Properties	Primary Actuation Stimulus	Common Fabrication Methods	Key Advantages	Critical Limitations
Silicone Elastomers	Polydimethylsiloxane (PDMS), Dragon Skin, Ecoflex	High elasticity ( strain), low modulus, biocompatible, thermally stable	N/A (Passive material)	Molding & Casting, 3D Printing (DIW)	Robust, versatile, low cost, well-understood	Poor adhesion, requires external actuation systems
Hydrogels	Polyacrylamide, Polyethylene glycol (PEG)	High water content (), tissue-like softness, biocompatible	Temperature, pH, light, electric/magnetic fields	Polymerization, cross-linking	Biomimetic, stimuli-responsive, ideal for medical use	Poor mechanical strength, slow response, dehydration in air
Shape-Memory Polymers (SMPs)	Polyurethane-based, Poly(ε-caprolactone)	Can be programmed with temporary shapes, lightweight	Heat (most common), light, electricity, moisture	3D Printing (4D Printing), Molding	Untethered actuation, programmable morphology, deployable	Slow response time, low force, often one-way effect, material fatigue
Electroactive Polymers (EAPs)	Dielectric Elastomers (DEs), Ionic Polymer-Metal Composites (IPMCs)	Change shape under electric field	Electricity	Film deposition, casting	Fast response, high energy density (DEs), low voltage (IPMCs)	High voltage requirement (DEs), low force, durability issues, dielectric breakdown
Liquid Crystal Elastomers (LCEs)	N/A	Anisotropic, programmable deformation	Heat, light	Synthesis, cross-linking	Large, complex, programmable shape changes	Difficult to synthesize, relatively slow actuation

Actuation and Control: The Challenge of Animating Softness

A robot’s utility is defined by its ability to move and interact with the world. For soft robots, whose bodies are continuously deformable and lack the rigid skeletons and discrete joints of their conventional counterparts, the challenges of actuation (generating motion) and control (directing that motion) are profound and deeply intertwined. Traditional robotic paradigms of motors and gearboxes are largely incompatible with the goal of a fully compliant system. This has spurred the development of novel actuation strategies, from fluid-powered artificial muscles to “smart” materials that move on their own. This section examines the primary methods used to animate soft robots, analyzing their operating principles, performance characteristics, and system-level constraints. It also confronts the core difficulty of the field: how to precisely control a system with near-infinite degrees of freedom and complex, non-linear dynamics.

Fluidic Power: Pneumatic and Hydraulic Actuation

The most prevalent and well-developed method for actuating soft robots is fluidic power, which uses a pressurized fluid—either a gas (pneumatics) or a liquid (hydraulics)—to deform the robot’s elastomeric structure.3

Design Principles: PneuNets, McKibben Muscles, and Beyond

Fluidic actuators are typically monolithic structures, often made of silicone, with embedded channels or bladders that expand when pressurized. The resulting motion is dictated by the actuator’s geometry and material composition. Several key designs have become foundational in the field:

Pneumatic Networks (PneuNets): This popular design, often used for bending actuators, features a series of interconnected chambers or bellows on one side of a beam-like structure. The other side is composed of a solid, inextensible, or “strain-limiting” layer.36 When pressurized air is introduced, the chambers expand, but since the bottom layer cannot stretch, the entire structure is forced to bend away from the expanding chambers.36 By arranging multiple, independently controlled PneuNets, complex multi-axis bending and manipulation can be achieved.
McKibben Actuators (Pneumatic Artificial Muscles – PAMs): One of the earliest soft actuators, the McKibben muscle consists of an internal inflatable bladder encased in a braided mesh sleeve.3 When the bladder is pressurized, it expands radially, forcing the braided mesh to shorten in length, much like a contracting biological muscle.38 PAMs are linear actuators that provide high force-to-weight ratios and are often used in agonist-antagonist pairs to mimic biological limb actuation.3
Fiber-Reinforced Actuators: This versatile approach involves strategically embedding inextensible fibers (such as aramid or nylon) into the walls of an elastomeric actuator.33 These fibers act as local constraints, preventing expansion in certain directions. For example, by wrapping fibers helically around a cylindrical chamber, inflation can be converted into a twisting motion. By orienting fibers along the length, radial expansion can be maximized while axial extension is minimized. This technique allows designers to program complex modes of deformation—bending, twisting, extending, or combinations thereof—into the actuator’s structure.38

Analysis of Advantages and System-Level Constraints

The dominance of fluidic actuation stems from a compelling set of advantages. Pneumatic systems, using air as the working fluid, are lightweight, inherently compliant due to the compressibility of air, capable of fast response times, and can be built from low-cost components.18 Hydraulic systems, using an incompressible liquid like water or oil, can generate much higher forces and offer the potential for more precise and smoother control, as the fluid volume directly corresponds to actuator displacement.34

However, these advantages are offset by a critical, system-level constraint: tethering. Both pneumatic and hydraulic systems require an off-board source of pressurized fluid—an air compressor or a hydraulic pump—as well as a network of tubes and valves to route the fluid to the actuators.7 These tethers severely limit the robot’s mobility, autonomy, and practical application in many real-world scenarios.34 The entire field of soft robot actuation can be viewed through the lens of this central challenge, with much of the research aimed at either miniaturizing the necessary hardware to be carried on-board or developing alternative actuation methods that eliminate the need for fluidic power altogether. Furthermore, the non-linear pressure-volume relationship and time delays in pneumatic systems make precise, closed-loop control notoriously difficult.9

Tendon-Driven Mechanisms: Mimicking Biological Musculature

An alternative approach, inspired by the anatomy of vertebrates, is tendon-driven actuation. In these systems, high-strength, flexible cables or “tendons” are routed through channels in the soft body of the robot.3 These tendons are connected to external motors (typically servomotors), which pull on them to induce bending, contraction, or stiffening.43

This method is particularly common in Articulated Soft Robots, a class of hybrid systems that combine rigid structural “bones” with compliant joints and actuators, directly mimicking the musculoskeletal architecture of animals.5 The tendons act like biological tendons, transmitting force from a remote “muscle” (the motor) to the desired point of action. This allows for the consolidation of heavy motors at the base of the robot, reducing the inertia of the moving limbs.

Tendon-driven actuation is highly effective for creating dexterous manipulators, such as robotic hands for rehabilitation or grasping.43 By using underactuation—where a smaller number of tendons controls a larger number of joints—the hand can passively adapt its shape to conform to an object, simplifying the grasping process.45 The primary trade-off is that while tendon systems can offer high dexterity and simplified control, they generally have a lower force and load-carrying capacity compared to high-pressure fluidic systems. The tether is also still present, though it takes the form of a mechanical cable rather than a fluid tube.

Direct Actuation with Smart Materials: The Untethered Frontier

The quest for truly autonomous and untethered soft robots has led to intense research into “smart materials” that function as actuators themselves, converting various forms of energy directly into mechanical motion. This approach eliminates the need for bulky external power transmission systems like pumps or motors. Key methods include:

Electrical Actuation: Electroactive Polymers (EAPs) like Dielectric Elastomers change shape when a high electric field is applied.12 They are fast and powerful but require high voltages, posing safety and power supply challenges.
Magnetic Actuation: By embedding ferromagnetic particles into a soft polymer matrix, the robot’s shape can be controlled remotely using an external magnetic field.12 This allows for wireless control but requires the robot to operate within the vicinity of a powerful magnetic field generator.
Thermal Actuation: Shape Memory Alloys (SMAs) and Shape Memory Polymers (SMPs) contract or recover a pre-programmed shape when heated.4 Heat is often generated by passing an electrical current through embedded resistive wires (Joule heating).48 While this enables electrical control, the process is often slow due to the time required for heating and cooling cycles, and it can be energy-inefficient.4
Chemical and Light Actuation: Certain hydrogels and polymers are designed to swell, shrink, or change shape in response to specific chemical cues (like pH) or light, offering another path to untethered actuation.12

The overarching advantage of smart material actuation is the potential for complete autonomy and miniaturization. However, this currently comes at a significant performance cost. Compared to fluidic systems, smart material actuators generally produce lower forces, have slower response times, and can suffer from material fatigue and lower energy efficiency.4

The Control Conundrum: Modeling and Managing Infinite Degrees of Freedom

The most formidable challenge in soft robotics is control. The very features that make soft robots advantageous—their material non-linearity, compliance, hysteresis, and infinite degrees of freedom—render traditional control methodologies, which are built on the rigid-body dynamics of discrete links and joints, largely ineffective.3

The core of the problem is the difficulty of creating an accurate predictive model of the robot’s behavior. The state of a soft robot cannot be described by a small set of joint angles; its shape is a continuous function that is difficult to measure and even harder to model, especially when it is interacting with its environment.6 For a soft manipulator, there is often no clear “end-effector” point whose position can be tracked, making it difficult to even define a task in traditional robotic terms.10

This “control conundrum” has pushed the field away from purely analytical, model-based control and toward more empirical, data-driven approaches. Instead of trying to derive a perfect mathematical model from first principles—a task that is often computationally intractable for real-time control—researchers are increasingly turning to machine learning.7 Techniques like imitation learning (or learning from demonstration) are particularly promising. In this paradigm, a human operator teleoperates the soft robot to perform a task, and a machine learning algorithm learns the mapping between sensor inputs and the required actuation signals. The robot learns the desired behavior by observing examples, bypassing the need for an explicit dynamic model.10

This highlights an essential co-design principle in soft robotics: the inverse relationship between embodied intelligence and control complexity. The more a robot’s physical body is designed to simplify a task through morphological computation, the less burden is placed on the explicit control algorithm.1 A well-designed soft gripper that passively adapts to objects requires a much simpler control signal (e.g., “open” or “close”) than a rigid hand that must precisely control the position and force of each finger. Therefore, solving the control problem in soft robotics is not just about writing better algorithms; it is about designing smarter bodies that make the control problem fundamentally easier to solve.

Actuation Method	Working Principle	Power Source	Key Design Examples	Performance: Speed	Performance: Force/Payload	Control Complexity	Tethering	Key Advantages	Critical Limitations
Pneumatic	Pressurized gas deforms elastomeric chambers	Air compressor	PneuNets, McKibben Muscles, Fiber-reinforced actuators	High	Medium to High	High (non-linear gas dynamics)	Yes (air tubes)	Fast, lightweight, compliant, low cost	Tethered, noisy, difficult to control precisely
Hydraulic	Pressurized liquid deforms elastomeric chambers	Hydraulic pump	Fluidic Elastomer Actuators (FEAs)	Medium	Very High	Medium (incompressible fluid)	Yes (liquid tubes)	High force, precise control, smooth motion	Tethered, risk of leaks, heavier than pneumatic
Tendon-Driven	Motors pull cables routed through the soft body	Electric motors	Articulated soft hands, continuum manipulators	High	Low to Medium	Medium	Yes (cables)	High dexterity, remote actuation, biomimetic	Lower payload, friction in tendons, mechanical complexity
Electroactive (EAP)	Electric field deforms polymer material	High-voltage power supply	Dielectric Elastomers (DEs), IPMCs	Very High	Low	High (non-linear electro-mechanics)	Yes (wires)	Very fast, silent, solid-state	Requires high voltage (DEs), low force, material degradation
Magneto-responsive	External magnetic field deforms embedded particles	External magnetic field generator	Untethered micro-robots, manipulators	Medium	Very Low	High (field control)	No (wireless)	Untethered, remote control	Low force, requires external field generator, limited range
Thermo-responsive	Heat triggers shape change in smart material	Electrical current (Joule heating)	Shape Memory Polymers (SMPs), Shape Memory Alloys (SMAs)	Very Low	Low to Medium	Low	Yes (wires, for heating)	Untethered actuation, programmable shape	Very slow (heating/cooling cycles), energy inefficient, material fatigue

Applications in Human-Centric Environments

The foundational principles of compliance and adaptability find their most compelling expression in applications where robots must operate in close proximity to, or in direct contact with, human beings. In these human-centric environments—from the operating room to the factory floor—the inherent safety of soft robotics is not just an advantage but a prerequisite. The ability of a soft robot to yield, deform, and absorb impact energy fundamentally changes the nature of human-robot interaction, enabling a level of collaboration and physical integration that is unattainable with rigid machines. This section explores the transformative impact of soft robotics in healthcare and collaborative manufacturing, providing detailed examples of how these systems are enhancing surgical procedures, revolutionizing rehabilitation, and creating safer, more versatile industrial automation.

Healthcare and Medicine: The Forefront of Safe Interaction

The medical field is a primary driver of soft robotics research, as the challenges of interacting with the delicate, complex, and variable structures of the human body align perfectly with the strengths of compliant systems. Soft robots offer the potential to create medical devices that are not only safer but also more effective and less invasive.

Surgical Robotics: Enhancing Minimally Invasive Procedures

Conventional surgical robots, while offering remarkable precision, are constructed from rigid materials that pose an inherent risk of inadvertent tissue damage through tearing or perforation.52 Soft robotics provides a safer alternative by using materials with mechanical properties that match those of soft biological tissues.52 This “compliance matching” minimizes stress concentrations at the tool-tissue interface, leading to gentler manipulation.54

Specific applications are rapidly emerging:

Soft Endoscopic and Catheter Systems: Traditional endoscopes and catheters are often rigid or have limited steerability, making navigation through tortuous anatomical pathways like the colon or blood vessels difficult and potentially traumatic for the patient.52 Soft, continuum robots, inspired by organisms like snakes or tentacles, can be designed to actively bend and steer their way through these complex environments with high dexterity, reducing tissue trauma and improving patient outcomes.55 For example, researchers are developing self-propelling endoscopic robots that can actively change their stiffness and shape to navigate the gastrointestinal tract.
Gentle Organ Manipulation: During laparoscopic surgery, the ability to gently grasp and retract delicate organs without causing damage is paramount. Soft robotic grippers and manipulators, often actuated pneumatically, can conform to the shape of an organ, distributing the gripping force over a wide area and enabling secure handling with minimal pressure.52
Intelligent Implantable Devices: The frontier of surgical soft robotics is moving beyond external tools to autonomous, implantable devices that can diagnose and treat from within the body. This represents a paradigm shift from a surgeon using an advanced “tool” to the deployment of an integrated “prosthetic” agent. A landmark study published in Science Robotics detailed a tiny, mechanically actuated soft device, the Dynamic Soft Reservoir (DSR), which uses micro-scale oscillations to actively modulate the body’s foreign body response. By preventing the formation of a dense fibrous capsule around an implant, the DSR can dramatically improve the long-term viability of devices like glucose sensors and drug delivery pumps.57 Another breakthrough, published in Nature Communications, showcased a skin-like, two-layer robot made of a hydrogel muscle and a polymer e-skin. This device can adhere to the surface of a beating heart, autonomously measure its electrical activity, and deliver therapeutic electrical stimulation, demonstrating a closed-loop sense-and-treat capability.58 This level of integration and autonomy points toward a future of intelligent medical implants that function as symbiotic partners with the body.

Rehabilitation and Assistive Devices: Wearable Robots for Human Augmentation

Soft robotics is uniquely suited for creating wearable devices for rehabilitation and human augmentation. Unlike rigid exoskeletons, which can be heavy, cumbersome, and kinematically constraining, soft robotic exosuits and orthotics are lightweight, comfortable, and conform to the user’s body, providing assistance without restricting natural movement.7 Their inherent compliance ensures that the interaction is safe and can be tailored to the specific needs and morphology of each patient.43

Key examples include:

Rehabilitation Gloves: For patients recovering from a stroke or other neurological injuries, regaining hand function is a critical goal. Soft robotic gloves, such as the “Exo-Glove,” use a series of soft pneumatic or tendon-driven actuators to gently move the patient’s fingers through flexion and extension exercises.43 This provides consistent, repetitive motion therapy that can help rebuild neural pathways and restore motor control.
Soft Exosuits for Gait Assistance: For individuals with mobility impairments, soft exosuits can provide assistance at key joints like the hip, knee, or ankle. The “Right Trousers” project, for instance, developed a wearable device with soft, inflatable air pockets and smart materials that contract to assist with movements like walking, standing up, and climbing stairs, helping elderly individuals maintain their independence.52
Cardiac and Organ Assist Devices: Beyond limbs, soft robotics is being applied to internal organs. Researchers have developed soft robotic sleeves that fit around a failing heart, contracting in sync with its natural rhythm to help pump blood, offering a less invasive alternative to traditional ventricular assist devices.32

The concept of safety in these applications is multidimensional. It encompasses not only the physical safety of preventing injury from impact but also the biomechanical safety of matching the body’s natural compliance to avoid long-term stress injuries.54 Furthermore, studies suggest a psychological dimension: the soft, non-threatening appearance and feel of these devices can reduce user anxiety and improve acceptance, a critical factor for devices intended for daily, intimate use.59

Collaborative Manufacturing: Gripping and Manipulation

While healthcare is a major focus, the most mature and commercially successful application of soft robotics to date is in industrial manufacturing, specifically for gripping and material handling.

Handling the Delicate and Irregular: Soft End-Effectors

In automated production lines, traditional rigid grippers, such as parallel-jaw grippers, are highly efficient but limited. They are designed for specific, known geometries and can easily damage fragile or compliant items.7 This is a major bottleneck in automating tasks in industries like food and beverage, consumer goods, and logistics, where products are often delicate, variable in shape and size, and easily bruised.

Soft robotic end-effectors, often attached as the “hand” on an otherwise rigid robotic arm, solve this problem elegantly.4 Typically made of silicone and actuated pneumatically, these grippers can passively conform to a wide variety of objects—from raw chicken to tomatoes to lightbulbs—without requiring complex vision systems or precise force control.7 This is a prime industrial example of morphological computation, where the gripper’s physical compliance simplifies the control problem. Companies like Soft Robotics Inc. have commercialized octopus-inspired grippers that are now widely used in food packaging and bin-picking applications, demonstrating the tangible economic value of the technology.8

The Future of Human-Robot Collaboration on the Factory Floor

The rise of soft robotics is poised to redefine the concept of the collaborative robot (cobot). While current cobots are designed with safety features like force sensors and rounded edges to allow them to work outside of cages, they are still fundamentally rigid machines whose potential for harm must be actively managed by complex software.12

By integrating soft components, particularly at the points of interaction, or by developing fully soft collaborative arms, the safety of the system becomes intrinsic rather than programmed.5 A soft robot arm can absorb an accidental impact, making the consequences of an unexpected collision far less severe. This enhanced safety could eliminate the need for protective barriers altogether, allowing for truly seamless and fluid collaboration between human workers and robotic assistants on shared tasks.3 This could increase productivity and flexibility in manufacturing and logistics, enabling automation of tasks that currently require human dexterity and judgment in close quarters.

Navigating the Unstructured World

Beyond the controlled confines of the factory and the clinic, the world is overwhelmingly unstructured, unpredictable, and complex. It is in these environments—the chaotic rubble of a disaster site, the delicate intricacies of a coral reef, the unexplored terrain of another planet—that the limitations of rigid robotics become most apparent and the unique advantages of soft robotics shine brightest. The ability of a soft robot to deform, squeeze, and adapt its form to its surroundings allows it to navigate and operate in settings where rigid machines would be immobile, ineffective, or destructive. This section explores how soft robotics is enabling new frontiers in search and rescue, environmental science, and space exploration.

Search, Rescue, and Disaster Response

In the aftermath of an earthquake, building collapse, or other disaster, the environment is a treacherous and unstructured maze of rubble, voids, and unstable debris. Search and rescue (SAR) operations in these conditions are dangerous and time-sensitive. Rigid robots can struggle to navigate such terrain; their fixed morphology prevents them from accessing tight spaces, and their weight and stiffness can cause further collapse.63

Soft robots offer a transformative solution for SAR missions.46 Their inherent compliance and deformability allow them to:

Penetrate Confined Spaces: Soft robots can squeeze, bend, and contort their bodies to navigate through narrow gaps and irregular voids in debris piles to search for survivors in areas inaccessible to humans or rigid machines.46
Traverse Unstable Terrain: Bio-inspired locomotion mechanisms, such as the peristaltic crawling of an earthworm or the undulating motion of a snake, enable soft robots to move effectively over uneven and unstable surfaces.11
Interact Safely: The compliant nature of a soft robot minimizes the risk of dislodging debris or causing further injury to trapped victims during exploration.46

Specific examples of soft robots for SAR are demonstrating this potential:

Vine-like “Growing” Robots: The Soft Pathfinding Robotic Observation Unit (SPROUT) is a prime example. It consists of a long, inflatable tube made of airtight fabric that “grows” or everts from its tip, extending deep into rubble piles.63 Steered by controlling air pressure, and equipped with a camera at its tip, SPROUT can explore and map voids, identify potential routes for rescuers, and locate survivors without applying significant force to the surrounding debris.63
Magnetically Actuated Micro-robots: Researchers are developing tiny, flexible robots embedded with magnetic particles. These robots can be remotely guided by an external magnetic field to crawl through rubble, and with integrated sensors, they can autonomously detect environmental cues like heat signatures from a survivor or obstacles in their path.47

A key insight from these applications is that for a soft robot in a cluttered environment, the acts of locomotion and manipulation are often inseparable. A vine robot moves by manipulating its surroundings—pushing aside small obstacles and physically probing the space ahead. An earthworm-like robot uses its entire body to grip and push against the terrain to propel itself forward. This contrasts sharply with traditional mobile robotics, where a distinct mobile platform carries a separate manipulator. For these soft systems, the environment is not an empty space to be traversed but a complex structure to be physically engaged with as the primary means of movement.

Environmental Monitoring and Scientific Exploration

The same properties that make soft robots ideal for SAR also make them excellent tools for exploring and monitoring delicate natural ecosystems with minimal disturbance.67 Their soft bodies are less likely to damage fragile structures like coral reefs or harm wildlife, enabling a new class of non-invasive scientific observation.

Underwater and Marine Exploration: A significant area of research focuses on bio-inspired underwater robots. By mimicking the forms and propulsion mechanisms of marine life, such as fish, rays, or octopuses, soft robots can achieve highly efficient and maneuverable swimming.7 These robots can be deployed to monitor the health of coral reefs, collect water samples, or study aquatic animal behavior without the noise and physical disruption caused by traditional propeller-driven autonomous underwater vehicles (AUVs).68 A recent breakthrough involves the development of miniature, insect-inspired robots that can walk on the surface of water. Created using a novel fabrication technique called “HydroSpread,” these tiny robots are ideal for surface-level water monitoring and sample collection in fragile or hazardous flooded areas.59
Environmental Cleanup: The adaptability of soft robots is also being explored for environmental remediation tasks. For example, soft grippers could be used to gently collect delicate debris from sensitive shorelines, or crawling robots could be deployed to navigate contaminated sites to perform measurements or cleanup.61

A crucial enabling factor for these applications is the potential for expendable exploration. The materials used in many soft robots—silicones, fabrics, and 3D-printed polymers—are often significantly less expensive than the precision-machined components, motors, and sensors of their rigid counterparts.38 This lower cost fundamentally changes the risk assessment for deploying robots into hazardous or remote environments. It becomes feasible to deploy swarms of low-cost, semi-expendable soft robots for tasks like large-area environmental monitoring or high-risk disaster response, where the loss of a few individual units would not compromise the overall mission—a strategy that is often financially prohibitive with multi-million-dollar rigid platforms.63

The Next Frontiers: Space and Subterranean Applications

The unique attributes of soft robotics are opening up possibilities for exploration in the most extreme and inaccessible environments.

Space Exploration: The field of space robotics is beginning to embrace soft systems for several key advantages. Their low mass reduces launch costs, and their ability to be compactly stowed and then deployed—for example, through inflatable structures—is ideal for volume-constrained spacecraft.71 Potential applications being actively researched include soft robotic grippers for collecting geological samples on other planets, manipulators for servicing and maintaining space infrastructure, and deployable habitats.68 The compliance of soft robots also makes them well-suited for interacting with delicate or unknown objects in extraterrestrial environments.
Subterranean and Agricultural Applications: The ability of some soft robots to burrow or grow through granular media like soil opens up future possibilities in mining, resource extraction, and agriculture.54 A robot that can navigate underground could be used for soil analysis, precision delivery of water and nutrients to plant roots, or exploration for mineral deposits.

In all these unstructured domains, from disaster zones to distant planets, soft robotics offers a compelling solution to the challenge of operating in the unknown. By replacing rigid certainty with compliant adaptability, these machines are poised to go where no robot has gone before.

Grand Challenges and Strategic Outlook

While the potential of soft robotics is vast, the field is still in its relative infancy, confronting a series of fundamental scientific and engineering challenges that must be overcome to translate laboratory prototypes into robust, real-world solutions. The very properties that define soft robots—their compliance and continuous deformability—are the source of their greatest strengths and their most profound difficulties. This final section provides a critical assessment of the key technical hurdles facing the field, explores the promising hybrid approach that combines soft and rigid elements, and offers a forward-looking perspective on the research trajectory and long-term societal impact of this transformative technology.

Overcoming Key Technical Hurdles: Durability, Power, Sensing, and Control

To achieve widespread adoption, the soft robotics community must address four interconnected grand challenges:

Durability and Robustness: Soft materials like silicones and hydrogels are inherently more susceptible to wear, tear, puncture, and degradation than the metals and hard plastics of conventional robots.7 This limited durability is a major barrier to their deployment in harsh industrial or field environments where they may be exposed to sharp objects, abrasive surfaces, or heavy loads.13 Enhancing material toughness and developing self-healing capabilities are critical areas of ongoing research.13
Power and Autonomy: The “tethering problem” remains one of the most significant obstacles to the mobility and autonomy of soft robots.21 High-performance fluidic systems require bulky, off-board compressors and pumps, while many electrically-driven smart materials demand high-voltage power supplies connected by wires.34 The development of compact, lightweight, and high-energy-density power sources that can be fully integrated into a soft body is a crucial research frontier. This includes work on soft batteries, micro-combustion systems, and chemical fuel sources that could enable long-duration, untethered operation.61
Sensing and Integration: To intelligently interact with their environment, soft robots need sophisticated sensory feedback. However, integrating sensors into a continuously deforming body without compromising its softness and flexibility is a major challenge.73 Conventional rigid sensors are often unsuitable. While soft sensors made from conductive elastomers or microfluidic channels are being developed, they can suffer from issues like signal drift, hysteresis (a lag in response), and low durability.4 Creating robust, high-density “robotic skins” that can sense pressure, strain, and temperature across the entire body is essential for achieving advanced control and safe interaction.68
Modeling and Control: As discussed previously, the control of soft robots is arguably the field’s most difficult problem. The infinite degrees of freedom, non-linear material properties, and complex fluid-structure interactions make it nearly impossible to create accurate, real-time predictive models for control.6 This limitation currently restricts most soft robots to simple, open-loop movements or tasks where precision is not required. Overcoming this will require a paradigm shift in control theory. The most viable path forward appears to be a synergistic approach that combines smarter physical design (morphological computation) with advanced, learning-based AI. By designing bodies that are physically predisposed to perform a task, the control problem becomes simpler. AI and machine learning can then be used to learn the remaining complexities of controlling this “good enough” system, bypassing the need for a perfect, but intractable, analytical model.10

The Hybrid Approach: Integrating Soft and Rigid Components

The recognition of these challenges has led to a growing consensus that the future of many practical robotic systems may not be “fully soft” but rather a strategic and intelligent integration of soft and rigid components.13 This hybrid approach seeks to combine the best of both worlds: the strength, speed, and precision of rigid robotics with the safety, adaptability, and dexterity of soft robotics.

Examples of this philosophy are already prevalent. Articulated soft robots use rigid links to provide skeletal support and strength, while employing compliant joints and soft actuators to provide fluid, life-like motion and impact absorption.5 The most common industrial application, the soft gripper, is itself a hybrid system, where a compliant end-effector is mounted on a conventional rigid robotic arm, combining the arm’s precise positioning with the gripper’s gentle and adaptable grasp.4 Designing these hybrid systems presents its own set of challenges, including how to seamlessly join dissimilar materials and how to coordinate control between the rigid and soft components.10 However, this approach offers a pragmatic pathway to leveraging the benefits of softness in applications that still require a degree of strength and precision.

The Future Trajectory: Autonomy, Material Intelligence, and Societal Impact

Looking ahead, the trajectory of soft robotics is evolving from simple bio-inspiration to deep bio-integration. The early phase of the field focused on mimicking the forms and movements of organisms like octopuses and worms.2 The next, more profound phase, particularly visible in medicine, is focused on creating soft robotic systems that can be directly and symbiotically integrated with living biological systems. The goal is no longer just to build a robot that looks like an animal, but to build a device that the human body accepts and cooperates with at a cellular level.57 This requires a deep, interdisciplinary fusion of robotics, materials science, and biology.

This evolution is being driven by several key trends:

Increasing Autonomy: Advances in AI, embedded control systems, and onboard power will continue to cut the tethers, leading to more capable and independent soft robots.61
Advanced Material Intelligence: The frontier of materials science is focused on creating “smarter” materials with faster response times, higher force output, multi-stimuli responsiveness, and self-healing properties that can enhance durability.13
Global R&D Ecosystem: Innovation is being accelerated by a vibrant global network of academic and industrial research labs, including prominent groups at institutions like Harvard University, MIT, ETH Zurich, Stanford University, and the University of Bristol, as well as commercial pioneers like Soft Robotics Inc..16

The long-term societal impact of these advancements is poised to be transformative. Soft robotics offers technological solutions to some of the most pressing global challenges, including supporting an aging population through safe assistive and nursing care robots, improving health outcomes with less invasive medical procedures, enhancing food security with gentle automated harvesting, and promoting environmental stewardship through non-invasive monitoring and cleanup.54

Concluding Analysis and Recommendations for R&D Focus

Soft robotics is a field of immense promise, offering a future where machines are no longer confined to cages but can work alongside us as safe partners, assist us as wearable extensions of our own bodies, and explore the world’s most delicate and dangerous corners on our behalf. Its core principles of compliance and embodied intelligence represent a fundamental and necessary evolution in robotics, enabling a new class of applications centered on interaction, adaptation, and safety.

However, the path from promise to widespread practice is contingent on solving the grand challenges of durability, power, sensing, and control. To accelerate this transition, a concerted and strategic focus on interdisciplinary research and development is required. Based on the analysis within this report, future R&D efforts should be prioritized across four critical domains:

Advanced Materials Science: The development of next-generation smart materials with higher energy efficiency, faster actuation speeds, greater force output, and intrinsic self-healing capabilities is paramount.
Integrated Power Systems: A dedicated push toward creating compact, high-energy-density, and fully soft power sources is essential to solve the tethering problem and unlock true autonomy.
Learning-Based Control Architectures: Research should continue to shift from perfecting traditional analytical models to advancing AI and machine learning frameworks specifically tailored for the control of high-dimensional, non-linear, deformable systems.
Hybrid System Design Principles: A systematic effort is needed to codify the design principles for optimally integrating soft and rigid components, enabling engineers to create hybrid robots that are more than the sum of their parts.

By focusing on these foundational pillars, the scientific and engineering communities can overcome the current limitations and fully unleash the revolutionary potential of soft robotics, shaping a future where technology is not only more intelligent but also softer, safer, and more seamlessly integrated with the human experience.

Cutting-edge Technology Courses by Uplatz