Engineers face a variety of challenges in achieving autonomy in soft robots. Soft robots, which are generally made from flexible materials that resemble natural organisms, are sought after for their ability to navigate complicated and dynamic environments, making them highly desirable for applications such as search and rescue missions, medical procedures, and exploration in space or underwater. However, their path to complete autonomy is strewn with obstacles.
One of the main difficulties in soft robotics is the inclusion of rigid components, such as power supplies, microcontrollers, motors, or air pumps. These rigid elements are the natural choices for providing energy, control, and movement to the soft body, but they inherently limit the robot's ability to adapt its shape to suit its task or environment. The rigid parts restrict the robot's flexibility and deformability, which can impair its performance in environments where maneuverability and adaptability are critical.
In an effort to address these limitations, researchers have explored alternative methods of actuation and control. Magnetic fields, for instance, have been utilized to manipulate soft robot components, offering a potential solution to the present reliance on internal rigid components. However, this approach requires the use of external equipment, such as magnetic coils, which presents a different set of problems. Achieving true autonomy becomes challenging when soft robots are tethered to external devices, as it restricts their ability to roam freely and operate independently in unstructured environments.
Building physical intelligence into a soft robot through careful consideration of both its structural design, and the materials that it is made of, is another potential avenue to achieving autonomy. A research group at North Carolina State University took this approach in creating a “brainless” maze-solving robot that they reported on last year. However, this robot proved to be a little bit too brainless, often getting stuck, tending to perpetually bounce back and forth between nearby obstacles.
Taking the lessons learned from that research, the team has now produced a more intelligent (yet still brainless) soft robot that can escape more complex mazes without losing its way. The worm-like robot, like its predecessor, is made from liquid crystal elastomers in a ribbon-like configuration. When this material is heated to a minimum of 131 degrees Fahrenheit by the surface it is on, it will contract. The other side of the material, which is exposed to air, will not reach the critical temperature.
As a result, the ribbons of elastomer will be of differing lengths in the body of the robot. This causes the robot to roll. Unlike the previous robot, this new version has different structural configurations in each half — in one half the ribbon is more tightly twisted, and also twists around itself in a helical manner. For this reason, each half rolls at a different rate, which acts something like a plastic cup on its side, rolling across a flat surface, making a gradual turning motion.
With this asymmetrical design, the robot can roll and bounce its way through a maze — eventually, anyway. The material may have some physical intelligence, but it is far from being at a genius level. It more or less blindly stumbles its way along until it achieves a goal that it was not aware of, and was not intentionally working towards.
There is also the matter of the differential heating of the material to consider. While the robot may appear to be operating autonomously, it does rely on a surface that is heated within a specific, acceptable range, and an air temperature above it that is cool enough for differential deformation of the material. That will certainly limit the areas where this technology could be applied. However, with future work, this material may someday be one crucial part of a complete solution to autonomy in soft robotics.