Flexible and stretchable sensors for fluidic elastomer actuated soft robots
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oduction Soft robotics, an emerging subfield of robotics, aims to provide simpler and more robust interactions with humans in complex and unpredictable environments. For our purposes, we define soft from a human perspective—as a structure that would deform readily upon the application of a contact pressure, which would typically cause harm to a user. There are two ways to achieve softness, extrinsically or intrinsically. Here, we will consider only the latter case: Robots that are soft regardless of their shape and are composed of elastomeric organic materials1–4 with tangent elastic moduli below 1 MPa (similar to that of the human skin epidermal layer of ∼100 kPa).5 These robots are able to demonstrate natural, continuous deformation with their mobility only limited by the extensibility of the constituent materials.1 Examples of the complex motions they demonstrate from simple fabrication and control inputs include bending, twisting, extension, and conformation to arbitrary geometries using infinite passive degrees of freedom.6,7 Variants of soft robots can be categorized by the actuation mechanisms used. In this article, we limit our focus to fluidic elastomer actuators (FEAs).8 The fabrication technique of these robots involves intentionally embedding interconnected channels in silicones or other elastomers.1,9–11 By simply
pressurizing via either gas (pneumatic)12–15 or liquid (hydraulic),7,16,17 the channels inflate in regions with lowest stiffness and generate complex shapes and motions in three-dimensional (3D) space.1 Recently, our group developed a new class of FEAs based on molding stochastic networks of open-cell organic elastomeric foams. Using this technique, we can now form complex 3D actuators without the need for 3D printed fugitive channels (ink scaffolds that can be removed afterward),18,19 or even without 3D printing at all.20 A characteristic of most soft robots is that they demonstrate complex motions through simple open-loop control,21 realizing complex tasks such as walking on irregular terrains,9 grasping unpredictable shapes,22 and manipulating fragile objects.1 This control mechanism, simple as it is, is unable to achieve accuracy, or actively interact with its environment— eliminating the possibility of autonomy.23 In order to continuously regulate the output signals based on external circumstances, closed-loop controls are necessary, where sensors are used to obtain information from the environment (exteroception) and also to monitor their internal states (proprioception).23 These data are subsequently provided to the controller to selfcorrect errors and yield smart human–robot interactions.24 Hence, sensors with high repeatability and resolution, fast speeds,
Shuo Li, Department of Materials Science and Engineering, Cornell University, USA; [email protected] Huichan Zhao, Sibley School of Mechanical and Aerospace Engineering, Cornell University, USA; [email protected] Robert F. Shepherd, Department of Materials Science and Engineering, Sibley School of Mechanical and Aerospace Engineering,
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