Color-based robotic sensor can detect multiple stimuli just like skin

When it comes to robotics, the search to create an artificial skin that behaves like the real thing has dominated many of scientists’ recent work in the field. Although they have made great strides in this area, they still struggle with one of skin key abilities: the capacity to detect multiple stimuli at the same time. Many different stimuli, one sensor Now, researchers at EPFL’s School of Engineering’s Reconfigurable Robotics Lab (RRL) of a sensor that can discern combinations of bending, stretching, compression, and temperature changes using color as the input data.

The invention is called ChromoSense and it uses different LED colors to communicate to the robot equipped with the sensor what stimuli are taking place. “Imagine you are drinking three different flavors of slushie through three different straws at once: the proportion of each flavor you get changes if you bend or twist the straws. This is the same principle that ChromoSense uses: it perceives changes in light traveling through the colored sections as the geometry of those sections deforms,” said lead researcher at RRL Jamie Paik.

“For soft robots to serve us better in our daily lives, they need to be able to sense what we are doing,” she continued. Past attempts to achieve this have relied on vision-based systems such as cameras which are inherently expensive and cumbersome and use processes which require collecting a vast amount of data and then analyzing it. ChromoSense, on the other hand, enables more targeted immediate readings of an environment and the sensor may be easily integrated into a variety of materials for many different activities.

Perhaps its most notable quality is its versatility with Paik claiming that “with our technology, anything can become a sensor as long as light can pass through it. ” However, ChromoSense’s capacity to feel several stimuli at once can be both a strength and a weakness, as clearly identifying simultaneously applied stimuli can be difficult and lead to inaccurate results. Working on sensing capabilities As such, the sensor is not yet ready for mass production.

It still needs a lot of work and Paik and her colleagues are exploring ways to improve the technique for sensing locally applied forces and the exact limits of a material when it changes shape. “If ChromoSense gains popularity and many people want to use it as a general-purpose robotic sensing solution, then I think further increasing the information density of the sensor could become a really interesting challenge,” she explained. Future applications of the technology include mobility-aiding exosuits and athletic gear or clothing, which could be designed to provide information on a wearer’s form and movements.

The study in Owing to the remarkable properties of the somatosensory system, human skin compactly perceives myriad forms of physical stimuli with high precision. Machines, conversely, are often equipped with sensory suites constituted of dozens of unique sensors, each made for detecting limited stimuli. Emerging high degree-of-freedom human-robot interfaces and soft robot applications are delimited by the lack of simple, cohesive, and information-dense sensing technologies.

Stepping toward biological levels of proprioception, we present a sensing technology capable of decoding omnidirectional bending, compression, stretch, binary changes in temperature, and combinations thereof. This multi-modal deformation and temperature sensor harnesses chromaticity and intensity of light as it travels through patterned elastomer doped with functional dyes. Deformations and temperature shifts augment the light chromaticity and intensity, resulting in a one-to-one mapping between stimulus modes that are sequentially combined and the sensor output.

We study the working principle of the sensor via a comprehensive opto-thermo-mechanical assay, and find that the information density provided by a single sensing element permits deciphering rich and diverse human-robot and robot-environmental interactions. .