A soft, amorphous skin that can sense and localize textures

Abstract

We present a soft, amorphous skin that can sense and localize textures. The skin consists of a series of sensing and computing elements that are networked with their local neighbors and mimic the function of the Pacinian corpuscle in human skin. Each sensor node samples a vibration signal at 1KHz, transforms the signal into the frequency domain, and classifies up to 15 textures using logistic regression. By measuring the power spectrum of the signal and comparing it with its local neighbors, computing elements can then collaboratively estimate the location of the stimulus. The resulting low-bandwidth information, consisting of the texture probability distribution and its location are then routed to a sink anywhere in the skin in a multi-hop fashion. We describe the design, manufacturing, classification, localization and networking algorithms and experimentally validate the proposed approach. In particular, we demonstrate texture classification with 71% accuracy and centimeter accuracy in localization over an area of approximately three square feet using ten networked sensor nodes.

Materials that couple sensing, actuation, computation, and communication

“…A system such as the sensing skin (15) illustrates this difficulty with respect to sensing, a shape-changing material such as (14) with respect to actuation, and the smart façade with respect to a combination of both. Routing vibration signals sampled at 1 kHz becomes increasingly difficult when the number of sensors increases.…”

“…Robotic materials integrate dedicated sensors that, in combination with appropriate signal processing, let the composite identify and respond to environmental patterns of arbitrary complexity, limited only by available sensors and computation. An example of complex signal processing that can be accomplished in a robotic material is to sense and localize textures that touch an artificial skin (15) (Fig. 2D).…”

“…Some example robotic materials that take extensive advantage of this feature are distributed gesture recognition in an amorphous façade (12), where local communication is used to pass tactile sensing events along the physical path where they occur; texture identification in a robotic skin (15), where local communication allows triplets of nodes to triangulate the location of a vibration event by comparing local measurements; and distributed sensor-based control of a rolling robot (62), where local communication is used to infer the overall orientation of the material with respect to the ground.…”

“…Examples of robotic materials that combine sensing, actuation, computation, and communication. (A) An amorphous façade that recognizes gestures and changes its opacity and color (12); (B) a dress that can localize sound sources and indicate their direction through vibro-tactile feedback (13); (C) a shape-changing variable stiffness beam (14); and (D) a robotic skin that senses touch and texture (15). of integrated computation that have been articulated by (16,18,31).…”

“…Examples shown in Fig. 2 include an amorphous façade that recognizes a user's input gestures and responds with changes in its opacity and color (12), a dress that can localize sound sources and indicate their direction using vibro-tactile feedback (13), a shapechanging variable stiffness beam (14), and a robotic skin that senses touch and texture (15).…”