Robots generally excel at specific tasks in structured environments but lack the versatility and the adaptability required to interact with and locomote within the natural world. To increase versatility in robot design, we present robotic skins that can wrap around arbitrary soft bodies to induce the desired motions and deformations. Robotic skins integrate actuation and sensing into a single conformable material and may be leveraged to create a multitude of controllable soft robots with different functions or gaits to accommodate the demands of different environments. We show that attaching the same robotic skin to a soft body in different ways, or to different soft bodies, leads to distinct motions. Further, we show that combining multiple robotic skins enables complex motions and functions. We demonstrate the versatility of this soft robot design approach in a wide range of applications—including manipulation tasks, locomotion, and wearables—using the same two-dimensional (2D) robotic skins reconfigured on the surface of various 3D soft, inanimate objects.

A robotic skin is a modular, 2D soft robot that can be reconfigured on the surface of passive, deformable bodies to produce deformations. Robotic skins can be assembled around different soft bodies in different orientations to produce a wide range of robotic systems. This class of robots holds potential for applications where operators need highly reconfigurable, lightweight robots to assist in variable tasks.

We introduce a soft robot design approach based on active robotic skins that manipulate soft, deformable bodies from their surface. Robotic skins are modular, conformable sheets with embedded sensing and actuation, which may be applied to, removed from, transferred between, and reoriented on the surface of soft bodies (e.g., inflatables, foams, and limbs) to impart motion onto those bodies. This surface-based approach allows any passive soft object to be turned into an active soft robot ( Fig. 1 ). Three principles enable multifunctional robot design with this approach: First, distinct motions may be achieved by reorienting a robotic skin on the surface of a soft body. Second, distinct motions may be achieved by wrapping a robotic skin around bodies with different properties and/or morphologies. Third, multiple robotic skins may be used in combination and reconfigured to perform different tasks. We demonstrated sensor-enabled closed-loop control of the robotic skins independent of specific actuator and substrate material choices. We further demonstrated transferability of the robotic skins between soft bodies to accomplish a wide variety of tasks, including an inchworm robot that was controlled either remotely by an operator or with onboard light sensors, a continuum manipulator that grasped and moved objects, an upper-body wearable garment that communicated posture information to a user, and a tensegrity structure that was surface-actuated using the robotic skins.

Robots are typically designed to perform a finite collection of tasks in a known context. This approach produces efficient solutions when the environment is structured and predictable. However, in many situations—such as exploration, search and rescue, or operating alongside humans—knowledge of the task to be performed, or the context in which it is to be performed, cannot be known a priori. One approach to alleviating this problem is the use of soft materials in robotics ( 1 – 3 ), where material deformation both enables damage-resilient soft robots ( 4 ) and allows simple designs to extend to multiple motion patterns ( 5 ). Soft robots have been shown to be advantageous for manipulation of delicate objects ( 6 , 7 ), compliance-matched for wearability ( 8 – 10 ), and able to withstand large impact forces ( 11 , 12 ). Soft robots have also been shown to achieve multiple locomotion gaits with the same structure, such as crawling and undulation of elastomeric robots ( 5 , 13 ) and hopping and rolling of spherical robots ( 14 , 15 ). Another soft robot was shown to perform both locomotion and grasping tasks ( 16 ). Multifunctionality in soft robots may be further enabled by modular and reconfigurable systems ( 13 , 17 , 18 ).

RESULTS

Design of robotic skins Robotic skins are two-dimensional (2D), fully controllable robotic systems that can deform soft objects from their surface. The objective of this work is to demonstrate the merits of this surface-based approach, without confining the concept to any one particular implementation. A large design space exists for robotic skins, which includes variation in components (actuators, sensors, and substrates), configuration (layout of components and geometry of the skin), and level of component integration. As examples, we fabricated three implementations of robotic skins. To show that different components can be used, we fabricated two implementations in a simple parallel component configuration but with different actuators and substrates. One of the implementations used pneumatic actuators integrated into an elastomer substrate (8), whereas the other used coiled shape memory alloy (SMA) actuators integrated onto a fabric substrate (19–21). Both implementations used conductive composite–based capacitive sensors (22). Because actuator choice dominates the overall performance of a robotic skin system, we refer to these two implementations as pneumatic skins and SMA skins. To show that different configurations can be used, we fabricated a third implementation in a triangular component configuration. This implementation included pneumatic actuators, a fabric substrate, and the same capacitive sensors. Triangulation of actuators produced biaxial strains and therefore accommodated compound curvature host bodies, whereas parallel actuators produced uniaxial strains and accommodated simpler, single curvature host bodies. Other possible configurations include multiple robotic skins that could be overlaid or other nonparallel actuator layouts, such as radial patterns or Cartesian grids. Further information on the materials, dimensions, and manufacture of the robotic skins can be found in Materials and Methods and in the Supplementary Materials.

Reorienting robotic skins on a soft body enabled distinct motions The first demonstrated principle of operation is that a robotic skin may be used in combination with a soft, deformable body, where attaching the same robotic skin to a soft body in different ways leads to distinct motions. We show a simple example of this principle by using a robotic skin with integrated actuation and sensing attached to a cylindrical foam body. By orienting the actuators along the length of the cylinder, linear contraction induced bending motion; by reorienting the actuators orthogonally, radial contraction induced compression (Fig. 2). Other motion primitives include axial extension, axial contraction, and torsion. Fig. 2 Operational concept. (A) Robotic skins embed distributed actuation and sensing into a conformable substrate. (B) Robotic skins may be wrapped around soft bodies to impart motion onto those bodies. (C) Robotic skins may be reoriented on a soft body to produce different forms of motion. (D) Multiple robotic skins can be combined into larger assemblies to produce complex motions.

Placing a robotic skin on different soft bodies affected motion The second principle we demonstrated is that using the same skin on soft bodies with different dimensions and mechanical responses yielded different motions. The motion achieved depends on the relationship between the dimensions, material properties, and force capabilities of the skin and the dimensions and stiffness characteristics of the body. We can leverage this codependence of the motion on both the skin’s capabilities and the body’s mechanical properties to create a variety of motions by reusing the same robotic skin. This concept is appealing because changing out the soft body to adjust the robot’s motion is often much simpler than altering the robotic components (actuators, sensors, and controllers). As an example, we focused on a continuum bending motion. By wrapping the same robotic skin around cylindrical foam bodies with different radii, we achieved different maximum deflections or workspaces. A robotic skin wrapped around a soft cylinder induced more deflection as the radius of the host cylinder decreased (Fig. 3), assuming homogeneous material properties and constant curvature (23). Further, by comparing the blocked force characteristics of a contraction actuator with the force required to deform the cylinder, we could predict the maximum deflection of the system. Figure 3A plots these forces for both the pneumatic and SMA actuators used in our implementations, as well as two foam cylinders with radii of 31.75 mm (1.25 in) and 44.45 (1.75 in). Figure 3B shows the intersections of the force curves, which indicate the maximum deflections achievable when pairing specific actuators with specific soft bodies. In our case, displacements of 27.4 mm (41.4° deflection) and 19.2 mm (29.3° deflection) were predicted for SMA actuators paired with the smaller and larger radius cylinders, respectively. Fig. 3 Robotic skins perform differently on different soft bodies. Here, soft cylinders of different radii will yield different maximum deflections (workspaces) for a bending segment. (A) By comparing the blocked force of the robotic skin actuators with the force required to deflect the soft cylinder, the maximum deflection may be predicted. The equilibrium points are highlighted in (B). Shaded regions around the means represent 95% confidence intervals. The above case highlights how a skin-body system can be designed to achieve a desired deformation. However, the skins may also be used on arbitrary soft bodies where the material properties are not known beforehand. Further details on the theoretical basis for predicting the deformation of bending systems composed of robotic skins and soft bodies with both known and unknown properties can be found in the Supplementary Materials.

Reconfiguring robotic skins and soft bodies enabled multifunctionality The third principle that we demonstrated is that multiple robotic skins may be used in combination to produce more complex motions and reconfigured for variable tasks (Fig. 4). After completing a task in one configuration, robotic skins can be removed and transferred to a different body to accomplish a different task. We demonstrated a simple case of this transferability by reconfiguring three robotic skins in combination with various cylindrical foam bodies to achieve three distinct functions. First, the skins were connected in series on a long foam body to create a multisegment continuum robot (Fig. 4, A to B). Second, the skins were separated and applied to new deformable bodies to produce different locomotion gaits (Fig. 4, C to H). Third, the skins were applied to a three-fingered end effector to demonstrate grasping (Fig. 4, I to L). These functions—continuum motion, locomotion, and grasping—were selected because they are often the building blocks used in complex robotic systems and can be leveraged to achieve a wide range of combinatorial tasks. Fig. 4 Modular robotic skins can be combined and/or reconfigured for various tasks. (A and B) Three robotic skins are linked together to form a continuum robot. These are then separated into three individual robotic skin modules and used to generate different locomotion gaits: (C and D) rowing locomotion, (E and F) inchworm locomotion, and (G and H) bodiless inchworm locomotion. (I to L) The three robotic skins are then transferred to a three-fingered grasping end effector, using one robotic skin per finger. Multisegment continuum robot By leveraging the bending motions previously described, multiple robotic skins can work in collaboration on a single body to achieve more complex motions. We demonstrated this by using three skins positioned on a long foam cylinder to form a three-segment continuum robot (Fig. 4, A and B). Design considerations, such as the number of skins and distance between them, may easily be modified, as well as the individual performance of each segment of the continuum robot system by using robotic skins with different actuators if desired. Locomotion robots The robotic skins are capable of producing many modes of locomotion. Here, we show three different gaits achieved by the pneumatic skins: rowing, inchworm, and bodiless inchworm. Additional gaits are presented in the Supplementary Materials. For all locomotion gaits demonstrated in Fig. 4, the actuators were pressurized at convenient rates (between 3 and 10 Hz) and pressures (140 kPa). The rowing gait was generated by attaching a skin to a foam cylinder with weighted end caps and cycling through the actuators (Fig. 4, C and D). Locomotion inspired by the inchworm (24, 25) was achieved by wrapping a skin around a foam cylinder with polystyrene “feet” on the ends (Fig. 4, E and F). We further generated a bodiless inchworm gait, which demonstrates that robotic skins with components tightly integrated into the substrate may operate independently of a host body (Fig. 4, G and H). To achieve bodiless inchworm locomotion, we simultaneously and cyclically contracted and then relaxed all of the skin’s actuators, resulting in repeated arching and flattening of the skin, and forward motion due to biased feet. In all cases, the locomotion gait and speed may be modified by tuning the skin-body interaction or parameters of the skin itself. Grasping end effector We further used the same robotic skins previously used for the three-segment continuum robot and three locomotion robots to demonstrate a three-fingered grasping end effector (Fig. 4, I to L). The skins were attached to foam cylinders bundled together, and high-friction pads were applied to each fingertip to increase contact friction with objects. To achieve the grasping motion, each skin bent its cylinder inward to grasp the object.

Closed-loop control of robotic skins We demonstrated sensor feedback and closed-loop control of systems using robotic skins (Fig. 5). In our implementations, we controlled the robotic skins by pairing each actuator with an off-board pressure or current controller and each sensor with an onboard signal conditioning circuit. Sensors and actuators were colocated in pairs and can be used to provide direct state feedback, rather than relying on inferential measures such as pressure or motion capture. This direct measurement approach has been enabled by recent advances in large-deformation strain-sensing technologies (26, 27). The sensors used in our implementations were made from a silicone composite that relies on expanded intercalated graphite (EIG) to achieve electrical conductivity (22). We used this conductive composite as the electrode material to fabricate high-deformation capacitive strain sensors with a linear relationship between capacitance and length (see fig. S8C). Sensor outputs during open-loop inchworm locomotion for both pneumatic and SMA skins are shown in Fig. 5 (A and B). Fig. 5 Onboard sensors enable state feedback and closed-loop control of robotic skins. (A and B) Sensor feedback during open-loop locomotion for both pneumatic and SMA skins positioned on soft cylinders. Actuation sequencing is shown in the cross-section schematics. (C and D) The state feedback from the sensors may be used for closed-loop control of cylinder deflection. Solid lines indicate the set point, dashed lines indicate the mean position, and clouds indicate the 95% confidence interval, over multiple trials. Five trials are shown for the pneumatic skin and 10 trials are shown for the SMA skin. The sensor information can be used to create sense-plan-act loops. To demonstrate these loops, we wrapped both the pneumatic and the SMA skins around a foam cylinder with a 31.75-mm (1.25-in) diameter. By controlling a single actuator, the robot was commanded to shorten one side of the body in a stair-step pattern (Fig. 5, C and D). We were able to consistently control the change in length of one side of the cylinder to a resolution of 1 mm, with an initial sensor length of 90 mm, with both types of skins. The pneumatic skin had its sensors bonded to its contraction-type McKibben actuators (which start in their extended, strain-limited state), and thus, its sensors can only contract. In contrast, the sensors in the SMA skin were not strain-limited by their corresponding actuators. When the SMA skin bent a deformable body, the sensor on the outer surface of the curved body was fully pressed against the body, therefore giving a reliable measure of the strain in the underlying surface. Therefore, in Fig. 5C, we plot the pneumatic skin’s set point as a contraction (the skin using an actuator to contract its underlying sensor), whereas in Fig. 5D, we plot the SMA skin’s set point as an extension (the skin using an actuator to stretch its opposing sensor). Because we measured the deformation of the surface of a body, our control algorithm was not dependent on the material or the dimensions of the underlying deformable body. Rather, the linear response of the sensors was used to infer the length of the underlying portion of the skin. For the SMA skin, we implemented a bang-bang control algorithm. For the pneumatic skin, a proportional-integral controller was used as an additional control loop to deal with the faster dynamics of the pneumatic system. The complete actuation time of the pneumatic actuators was on the order of 20 ms, relative to an actuation time of a few seconds for the SMA actuators. The actuator dynamics are detected by the sensors, which have a sample time on the order of 4 ms. Further information about the control algorithms can be found in the Supplementary Materials.