Inside a lab in Boston College’s Faculty of Engineering, a robotic arm drops small, plastic objects right into a field positioned completely on the ground to catch them as they fall. One after the other, these tiny constructions — feather-light, cylindrical items, no greater than an inch tall — fill the field. Some are pink, others blue, purple, inexperienced, or black.
Every object is the results of an experiment in robotic autonomy. By itself, studying because it goes, the robotic is looking for, and attempting to make, an object with probably the most environment friendly energy-absorbing form to ever exist.
To do that, the robotic creates a small plastic construction with a 3D printer, information its form and dimension, strikes it to a flat steel floor — after which crushes it with a stress equal to an grownup Arabian horse standing on 1 / 4. The robotic then measures how a lot power the construction absorbed, how its form modified after being squashed, and information each element in an enormous database. Then, it drops the crushed object into the field and wipes the steel plate clear, able to print and check the following piece. It is going to be ever-so-slightly completely different from its predecessor, its design and dimensions tweaked by the robotic’s laptop algorithm based mostly on all previous experiments — the idea of what is referred to as Bayesian optimization. Experiment after experiment, the 3D constructions get higher at absorbing the affect of getting crushed.
These experiments are doable due to the work of Keith Brown, an ENG affiliate professor of mechanical engineering, and his staff within the KABlab. The robotic, named MAMA BEAR — brief for its prolonged full title, Mechanics of Additively Manufactured Architectures Bayesian Experimental Autonomous Researcher — has advanced because it was first conceptualized by Brown and his lab in 2018. By 2021, the lab had set the machine on its quest to make a form that absorbs probably the most power, a property often known as its mechanical power absorption effectivity. This present iteration has run constantly for over three years, filling dozens of containers with greater than 25,000 3D-printed constructions.
Why so many shapes? There are numerous makes use of for one thing that may effectively take in power — say, cushioning for delicate electronics being shipped internationally or for knee pads and wrist guards for athletes. “You possibly can draw from this library of information to make higher bumpers in a automobile, or packaging gear, for instance,” Brown says.
To work ideally, the constructions must strike the right stability: they can not be so sturdy that they trigger harm to no matter they’re supposed to guard, however needs to be sturdy sufficient to soak up affect. Earlier than MAMA BEAR, the perfect construction anybody ever noticed was about 71 p.c environment friendly at absorbing power, says Brown. However on a cold January afternoon in 2023, Brown’s lab watched their robotic hit 75 p.c effectivity, breaking the recognized report. The outcomes have simply been printed in Nature Communications.
“Once we began out, we did not know if there was going to be this record-breaking form,” says Kelsey Snapp (ENG’25), a PhD scholar in Brown’s lab who oversees MAMA BEAR. “Slowly however certainly we stored inching up, and broke by way of.”
The record-breaking construction appears to be like like nothing the researchers would have anticipated: it has 4 factors, formed like skinny flower petals, and is taller and narrower than the early designs.
“We’re excited that there is a lot mechanical information right here, that we’re utilizing this to be taught classes about design extra typically,” Brown says.
Their intensive information is already getting its first real-life utility, serving to to tell the design of recent helmet padding for US Military troopers. Brown, Snapp, and undertaking collaborator Emily Whiting, a BU Faculty of Arts & Sciences affiliate professor of laptop science, labored with the US Military and went by way of discipline testing to make sure helmets utilizing their patent-pending padding are comfy and supply adequate safety from affect. The 3D construction used for the padding is completely different from the record-breaking piece — with a softer middle and shorter stature to assist with consolation.
MAMA BEAR just isn’t Brown’s solely autonomous analysis robotic. His lab has different “BEAR” robots performing completely different duties — just like the nano BEAR, which research the way in which supplies behave on the molecular scale utilizing a expertise referred to as atomic pressure microscopy. Brown has additionally been working with Jörg Werner, an ENG assistant professor of mechanical engineering, to develop one other system, often known as the PANDA — brief for Polymer Evaluation and Discovery Array — BEAR to check hundreds of skinny polymer supplies to seek out one which works finest in a battery.
“They’re all robots that do analysis,” Brown says. “The philosophy is that they are utilizing machine studying along with automation to assist us do analysis a lot sooner.”
“Not simply sooner,” provides Snapp. “You are able to do stuff you could not usually do. We will attain a construction or objective that we would not have been capable of obtain in any other case, as a result of it might have been too costly and time-consuming.” He has labored intently with MAMA BEAR because the experiments started in 2021, and gave the robotic its capacity to see — often known as machine imaginative and prescient — and clear its personal check plate.
The KABlab is hoping to additional reveal the significance of autonomous analysis. Brown needs to maintain collaborating with scientists in numerous fields who want to check extremely massive numbers of constructions and options. Though they already broke a report, “we’ve got no capacity to know if we have reached the utmost effectivity,” Brown says, which means they may presumably break it once more. So, MAMA BEAR will carry on operating, pushing boundaries additional, whereas Brown and his staff see what different functions the database will be helpful for. They’re additionally exploring how the greater than 25,000 crushed items will be unwound and reloaded into the 3D printers so the fabric will be recycled for extra experiments.
“We will hold learning this method, as a result of mechanical effectivity, like so many different materials properties, is barely precisely measured by experiment,” Brown says, “and utilizing self-driving labs helps us decide the perfect experiments and carry out them as quick as doable.”