New Automated System Creates Complex Robotic Parts

MIT researchers have developed a unique automated system that is capable of designing and 3D printing intricate robotic parts known as actuators. These actuators are optimized in accordance with a large number of specifications.

A new MIT-invented system automatically designs and 3-D prints complex robotic actuators optimized according to an enormous number of specifications, such as appearance and flexibility. To demonstrate the system, the researchers fabricated floating water lilies with petals equipped with arrays of actuators and hinges that fold up in response to magnetic fields run through conductive fluids. (Image credit: Subramanian Sundaram)

In brief, the system can do tasks automatically that are almost impossible for humans to do manually. In a paper recently reported in Science Advances, the scientists described the system by creating actuators that portray different types of black-and-white images at different angles. Actuators are basically devices that mechanically handle robotic systems in response to electrical signals.

For example, a single actuator shows a Vincent van Gogh portrait when laid flat. However, when it was activated and tilted an angle, it depicts the famous Edvard Munch painting called “The Scream.” In addition, the team 3D printed floating water lilies with petals integrated with arrays of hinges and actuators that fold up in response to magnetic fields running through conductive fluids.

The actuators are created from a patchwork of three varied materials, each having a different dark or light color as well as a property—like magnetization and flexibility—that regulates the angle of the actuator in response to a control signal. At first, the actuator design is broken down into an infinite number of 3D pixels, or “voxels” by the software. Any of the materials can be used to fill each 3D pixel.

The software then runs a countless number of simulations and uses different materials to fill different voxels. Next, it creates two different images at two different angles after landing on the optimal placement of each material contained in each voxel. Finally, a custom 3D printer drops the right material into the right voxel to construct the actuator in a layer-by-layer fashion.

Our ultimate goal is to automatically find an optimal design for any problem, and then use the output of our optimized design to fabricate it. We go from selecting the printing materials, to finding the optimal design, to fabricating the final product in almost a completely automated way.

Subramanian Sundaram, Study First Author and Former Graduate Student, Computer Science and Artificial Intelligence Laboratory, MIT

The changing images show what the system is capable of doing. However, actuators developed specifically for function and appearance can also be employed for biomimicry in robotics. For example, other scientists are developing underwater robotic skins equipped with actuator arrays intended to imitate denticles on shark skin. Together, denticles deform to reduce drag for quieter and faster swimming.

You can imagine underwater robots having whole arrays of actuators coating the surface of their skins, which can be optimized for drag and turning efficiently, and so on,” stated Sundaram.

The paper is also contributed by Melina Skouras, a former MIT postdoc; Louise van den Heuvel ’14, SM ’16; David S. Kim, a former researcher in the Computational Fabrication Group; and Wojciech Matusik, an MIT associate professor in electrical engineering and computer science and head of the Computational Fabrication Group.

Navigating the “Combinatorial Explosion”

Currently, robotic actuators are becoming more and more complex. Based on the type of application, these robotic actuators should be optimized for power consumption, flexibility, appearance, efficiency, weight, and numerous other performance and function metrics. In general, experts physically compute all those parameters to arrive at an optimal design.

Further adding to that complexity, the latest 3D-printing methods can currently utilize various materials to produce a single product. That means, the dimensionality of the design turns out to be exceptionally high.

What you’re left with is what’s called a ‘combinatorial explosion,’ where you essentially have so many combinations of materials and properties that you don’t have a chance to evaluate every combination to create an optimal structure.

Subramanian Sundaram, Study First Author and Former Graduate Student, Computer Science and Artificial Intelligence Laboratory, MIT

The scientists, in their work¸ initially modified three polymer materials with certain characteristics—rigidity, magnetization, and color—required to fabricate their actuators. The researchers eventually created a near-transparent rigid material—a kind of opaque flexible material that is utilized as a hinge, and a brown-colored nanoparticle material that reacts to a magnetic signal. The team then plugged all that characterization data within a property library.

The system takes grayscale image examples as input—for example, the flat actuator displaying the Van Gogh portrait but tilting at a precise angle to display “The Scream.” It fundamentally performs a complicated form of trial and error that is similar to rearranging a Rubik’s Cube. However, in this case, about 5.5 million voxels are iteratively reconfigured to correlate an image and fulfill a measured angle.

At first, the system arbitrarily assigns different materials to different voxels by drawing from the property library. It subsequently runs a simulation to see whether that arrangement displays both the target images, directly on and at an angle. In case that does not happen, it will receive an error signal, which allows it to know which voxels should be changed and which are on the mark.

For example, removing, adding, and shifting around brown magnetic voxels will alter the angle of the actuator upon applying a magnetic field; however, the system also needs to consider how the alignment of those brown voxels will have an impact on the image.

Voxel by voxel

In order to estimate the appearances of the actuator at each iteration, the investigators used a computer graphics method known as “ray-tracing”. This method replicates the path of light communicating with objects. The light beams, thus simulated, travel through the actuator at every column of voxels. It is possible to construct actuators with more than 100 voxel layers. Columns comprise over 100 voxels, with varied sequences of the materials radiating a different shade of gray when at an angle or flat.

For example, when the actuator is flat, the light beam might shine down on a column comprising several brown voxels, creating a dark tone. However, the beam will shine on misaligned voxels when the actuator tilts.

While brown voxels may move away from the beam, more clear voxels may move within the beam, creating a lighter tone. That method is utilized by the system to align both light and dark voxel columns where they have to be in the angled and flat image. Following 100 million or more iterations, and anywhere between a few and dozens of hours, the system will detect an arrangement that precisely fits the target images.

We’re comparing what that [voxel column] looks like when it’s flat or when it’s titled, to match the target images. If not, you can swap, say, a clear voxel with a brown one. If that’s an improvement, we keep this new suggestion and make other changes over and over again.

Subramanian Sundaram, Study First Author and Former Graduate Student, Computer Science and Artificial Intelligence Laboratory, MIT

In order to construct the actuators, the scientists created a custom 3D printer that utilizes a method known as “drop-on-demand.” Then, tubs of the three materials were linked to print heads with many numbers of nozzles that can be controlled separately.

A 30-micron-sized droplet of the designated material is fired into its respective voxel site by the printer. The droplet solidifies as soon as it lands on the substrate. In that manner, the printer constructs an object, in a layer-by-layer fashion.

The latest study can be utilized as a stepping stone for creating structures of larger size, for example, airplane wings, stated Sundaram. Scientists, for example, have likewise started to break down the airplane wings into tinier voxel-like blocks so as to improve their designs for lift, weight, and other metrics.

We’re not yet able to print wings or anything on that scale, or with those materials. But I think this is a first step toward that goal,” concluded Sundaram.


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