Ben Evans contributes to international collaboration advancing self-aware soft robots

Featured on the cover of Advanced Materials, the work is the first demonstration of a soft magnetic robot that can sense its own position within its environment.

“Soft” robots are emerging as a new class of machines that can flex and deform in ways that have been inaccessible to traditional robotics. These new motions can augment the capabilities of current devices – softer grasping can pick out blueberries in a production line; deformable bodies can wriggle through tight spaces – or they may lead to new capabilities yet to be imagined.

Like any robot, soft robotic devices are built to manipulate their environment. By their very nature, however, soft robots are also affected by their surroundings. This is a strength that enables novel interactions, but since the robot is no longer rigid, it may lose track of its own conformational awareness; that is, it may be unable to determine its own state, or its configuration in space. Most animals manage this challenge with the physiological sense of proprioception, or positional awareness. A central challenge of soft robotics is to instill flexible autonomous devices with a similar self-awareness.

To address this challenge, researchers in Intelligent Materials and Systems at Helmholtz-Zentrum Dresden Rossendorf (HZDR) developed an ultra-thin electronic skin that senses magnetic fields. When incorporated in a soft magnetic robot, the skin can sense and report the intensity and direction of the local magnetic field. This can imbue the device with an understanding of where it is in relation to itself – whether and how far, for example, an arm is bent – and the device may in principle build its own sense of proprioception.

Collaborating with researchers from North Carolina State University and Elon University, the team built and modeled a prototypical self-aware soft robot consisting of four folding arms. Experts in materials engineering at NCSU provided smart magnetic polymers that can soften and stiffen in response to light, while Elon Professor of Physics Ben Evans developed theoretical models to describe and predict the behavior of the device. Predictive models such as these are essential to developing a concept beyond the prototype stage. By understanding the physical laws governing an initial device, researchers can predict with confidence the behavior of an entire class of robot, enabling rapid optimization and development of subsequent generations.

This first report of a self-aware magnetic soft robot appeared in the June 24 issue of Advanced Materials.