Self-sculpting smart sand could assemble itself into solid replicas of objects

Research currently underway at MIT’s Distributed Robotic Laboratory (DRL) could lead to an innovative replicative manufacturing technique with the disruptive potential equal to that of 3D printing. Imagine a sand-like material that could autonomously assemble itself into a replica of any object encased within. Incredible though this may sound, the DRL researchers have already managed to build a large scale proof-of-concept, with 10-mm cubes acting as the grains.

Before we go into how these cubes - or "smart pebbles" - work, let’s sketch out the general concept. The idea is to create objects using a subtractive method, where excess material is removed just like when carving in stone. Each grain of smart sand would be a self-contained micro computer. These tiny machines would use an elaborate algorithm to communicate with the neighboring particles in order to establish the exact position and shape of the input object so that it can be replicated.

The already mentioned smart pebbles demonstrate this principle in a more easily understandable 2D setting. First the pebbles establish which of them border on the perimeter of the object to be replicated. Once identified, these particles pass on a message to their neighbors, and effectively specific particles selected by the algorithm are notified that an identical (or scaled) arrangement should be recreated a safe distance away, so that the two shapes do not overlap.

Once the perimeter of the copy is identified, the pebbles within that area bond to each other, while the redundant material simply falls away. The resultant object would be solid, but it could be easily deconstructed simply by putting it back into the heap of smart sand. The constituent grains would detach from each other and the whole process could be repeated with an entirely new shape.

Each smart pebble cube used for testing was equipped with a set of electro-permanent magnets on four sides. The magnetic properties of such magnets can be switched on and off using electrical impulses, but unlike electromagnets, they do not require electricity to sustain these properties over time. With each particle neighboring on eight other particles in a 2D scenario, the magnets allow for selective bonding with any of the neighbors. However, the magnets also play a role in communication and power sharing.

Each smart pebble was also fitted with a rudimentary microprocessor capable of storing 32 kilobytes of code and boasting two kilobytes of working memory. With such limited processing power at the disposal of a single unit, the main computational heft had to fall on the distributed intelligence algorithm that constitutes the core of the current DRL endeavors.

"How do you develop efficient algorithms that do not waste any information at the level of communication and at the level of storage?" asks Daniela Rus, a computer science and engineering professor at MIT. The answer to that question is likely to be found in a paper that Rus co-authored with her student, Kyle Gilpin, and which is going to be presented in May at the IEEE International Conference on Robotics and Automation.

The algorithms developed at DRL have already been shown to work robustly with 3D scenarios, where the bed of smart sand would be divided into layers, each constituting a separate 2D grid. Now the only thing that stops smart sand from joining 3D printing in revolutionizing the world of rapid manufacturing is getting the scale right.

But according to Robert Wood, an associate professor of electrical engineering at Harvard University, this is not an issue. Wood reckons recreating the functionalities of the smart pebbles in smaller scale is feasible. Yes, it would require quite a lot of engineering, but the goal is well defined and reachable. “That’s a well-posed but very difficult set of engineering challenges that they could continue to address in the future.”, he says. If Wood is right, the future of subtractive manufacturing is bright.

Watch the video below to find out more about the algorithm behind smart pebbles.

Source: MIT