MAGNETIC MODULAR ROBOTS
Self-propelled robotic cubes can form into structures
by Ben Coxworth / October 3, 2013
Imagine if an army of completely flat-faced cubes could roll around and even jump on their own, joining with one another to form a variety of large-scale structures. Well, that’s exactly what a team of robotics researchers at MIT are trying to turn into a reality – and they’ve already developed the cubes that could do it. Known as M-Blocks, the devices were created by MIT’s John Romanishin, Daniela Rus and Kyle Gilpin. Along with electronics that allow them to orient themselves relative to one another, each cube also contains a motor-driven flywheel, that spins at speeds of up to 20,000 rpm. When that flywheel suddenly brakes, the transfered momentum sends the cube flying in the direction that the wheel was spinning. Because the cubes additionally have magnets on each of their faces, they stick to one another when they make contact, until the flywheel in one sends it on its way again.
In order to make sure that the magnets of any two cubes meet north-pole-to-south-pole, the magnets themselves are cylindrical, and mounted in such a way that they can roll in place. If the magnets on two cubes are brought together north-to-north or south-to-south, the resulting repellant force will cause them to turn until their north and south poles are facing one another – at which point they’ll join together. In their current prototype form, the M-Blocks can roll across the ground, jump into the air, climb over each other, and even move while suspended upside-down. The researchers are now creating a group of 100 of the cubes, and plan on making more. It is hoped that eventually, swarms of their descendants could be deployed to perform services such as repairing buildings or bridges at disaster sites, performing reconnaissance in hazardous environments, or forming into scaffolding at construction sites. At that point in their development, some M-Blocks might be equipped with specialized features, such as cameras, battery packs, lights or sensors.
Surprisingly simple scheme for self-assembling robots
by Larry Hardesty / October 4, 2013
In 2011, when an MIT senior named John Romanishin proposed a new design for modular robots to his robotics professor, Daniela Rus, she said, “That can’t be done.” Two years later, Rus showed her colleague Hod Lipson, a robotics researcher at Cornell University, a video of prototype robots, based on Romanishin’s design, in action. “That can’t be done,” Lipson said. In November, Romanishin — now a research scientist in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) — Rus, and postdoc Kyle Gilpin will establish once and for all that it can be done, when they present a paper describing their new robots at the IEEE/RSJ International Conference on Intelligent Robots and Systems.
Known as M-Blocks, the robots are cubes with no external moving parts. Nonetheless, they’re able to climb over and around one another, leap through the air, roll across the ground, and even move while suspended upside down from metallic surfaces. Inside each M-Block is a flywheel that can reach speeds of 20,000 revolutions per minute; when the flywheel is braked, it imparts its angular momentum to the cube. On each edge of an M-Block, and on every face, are cleverly arranged permanent magnets that allow any two cubes to attach to each other. “It’s one of these things that the [modular-robotics] community has been trying to do for a long time,” says Rus, a professor of electrical engineering and computer science and director of CSAIL. “We just needed a creative insight and somebody who was passionate enough to keep coming at it — despite being discouraged.”
As Rus explains, researchers studying reconfigurable robots have long used an abstraction called the sliding-cube model. In this model, if two cubes are face to face, one of them can slide up the side of the other and, without changing orientation, slide across its top. The sliding-cube model simplifies the development of self-assembly algorithms, but the robots that implement them tend to be much more complex devices. Rus’ group, for instance, previously developed a modular robot called the Molecule, which consisted of two cubes connected by an angled bar and had 18 separate motors. “We were quite proud of it at the time,” Rus says. According to Gilpin, existing modular-robot systems are also “statically stable,” meaning that “you can pause the motion at any point, and they’ll stay where they are.” What enabled the MIT researchers to drastically simplify their robots’ design was giving up on the principle of static stability. “There’s a point in time when the cube is essentially flying through the air,” Gilpin says. “And you are depending on the magnets to bring it into alignment when it lands. That’s something that’s totally unique to this system.” That’s also what made Rus skeptical about Romanishin’s initial proposal. “I asked him build a prototype,” Rus says. “Then I said, ‘OK, maybe I was wrong.’”
Sticking the landing
To compensate for its static instability, the researchers’ robot relies on some ingenious engineering. On each edge of a cube are two cylindrical magnets, mounted like rolling pins. When two cubes approach each other, the magnets naturally rotate, so that north poles align with south, and vice versa. Any face of any cube can thus attach to any face of any other. The cubes’ edges are also beveled, so when two cubes are face to face, there’s a slight gap between their magnets. When one cube begins to flip on top of another, the bevels, and thus the magnets, touch. The connection between the cubes becomes much stronger, anchoring the pivot. On each face of a cube are four more pairs of smaller magnets, arranged symmetrically, which help snap a moving cube into place when it lands on top of another. As with any modular-robot system, the hope is that the modules can be miniaturized: the ultimate aim of most such research is hordes of swarming microbots that can self-assemble, like the “liquid steel” androids in the movie “Terminator II.” And the simplicity of the cubes’ design makes miniaturization promising. But the researchers believe that a more refined version of their system could prove useful even at something like its current scale. Armies of mobile cubes could temporarily repair bridges or buildings during emergencies, or raise and reconfigure scaffolding for building projects. They could assemble into different types of furniture or heavy equipment as needed. And they could swarm into environments hostile or inaccessible to humans, diagnose problems, and reorganize themselves to provide solutions.
Strength in diversity
The researchers also imagine that among the mobile cubes could be special-purpose cubes, containing cameras, or lights, or battery packs, or other equipment, which the mobile cubes could transport. “In the vast majority of other modular systems, an individual module cannot move on its own,” Gilpin says. “If you drop one of these along the way, or something goes wrong, it can rejoin the group, no problem.” “It’s one of those things that you kick yourself for not thinking of,” Cornell’s Lipson says. “It’s a low-tech solution to a problem that people have been trying to solve with extraordinarily high-tech approaches. What they did that was very interesting is they showed several modes of locomotion,” Lipson adds. “Not just one cube flipping around, but multiple cubes working together, multiple cubes moving other cubes — a lot of other modes of motion that really open the door to many, many applications, much beyond what people usually consider when they talk about self-assembly. They rarely think about parts dragging other parts — this kind of cooperative group behavior.” In ongoing work, the MIT researchers are building an army of 100 cubes, each of which can move in any direction, and designing algorithms to guide them. “We want hundreds of cubes, scattered randomly across the floor, to be able to identify each other, coalesce, and autonomously transform into a chair, or a ladder, or a desk, on demand,” Romanishin says.
by Larry Hardesty / April 2, 2012
Imagine that you have a big box of sand in which you bury a tiny model of a footstool. A few seconds later, you reach into the box and pull out a full-size footstool: The sand has assembled itself into a large-scale replica of the model. That may sound like a scene from a Harry Potter novel, but it’s the vision animating a research project at the Distributed Robotics Laboratory (DRL) at MIT’s Computer Science and Artificial Intelligence Laboratory. At the IEEE International Conference on Robotics and Automation in May — the world’s premier robotics conference — DRL researchers will present a paper describing algorithms that could enable such “smart sand.” They also describe experiments in which they tested the algorithms on somewhat larger particles — cubes about 10 millimeters to an edge, with rudimentary microprocessors inside and very unusual magnets on four of their sides. Unlike many other approaches to reconfigurable robots, smart sand uses a subtractive method, akin to stone carving, rather than an additive method, akin to snapping LEGO blocks together. A heap of smart sand would be analogous to the rough block of stone that a sculptor begins with. The individual grains would pass messages back and forth and selectively attach to each other to form a three-dimensional object; the grains not necessary to build that object would simply fall away. When the object had served its purpose, it would be returned to the heap. Its constituent grains would detach from each other, becoming free to participate in the formation of a new shape.
Algorithmically, the main challenge in developing smart sand is that the individual grains would have very few computational resources. “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 professor of computer science and engineering at MIT and a co-author on the new paper, together with her student Kyle Gilpin. If every grain could simply store a digital map of the object to be assembled, “then I can come up with an algorithm in a very easy way,” Rus says. “But we would like to solve the problem without that requirement, because that requirement is simply unrealistic when you’re talking about modules at this scale.” Furthermore, Rus says, from one run to the next, the grains in the heap will be jumbled together in a completely different way. “We’d like to not have to know ahead of time what our block looks like,” Rus says. Conveying shape information to the heap with a simple physical model — such as the tiny footstool — helps address both of these problems. To get a sense of how the researchers’ algorithm works, it’s probably easiest to consider the two-dimensional case. Picture each grain of sand as a square in a two-dimensional grid. Now imagine that some of the squares — say, in the shape of a footstool — are missing. That’s where the physical model is embedded. According to Gilpin — lead author on the new paper — the grains first pass messages to each other to determine which have missing neighbors. (In the grid model, each square could have eight neighbors.) Grains with missing neighbors are in one of two places: the perimeter of the heap or the perimeter of the embedded shape. Once the grains surrounding the embedded shape identify themselves, they simply pass messages to other grains a fixed distance away, which in turn identify themselves as defining the perimeter of the duplicate. If the duplicate is supposed to be 10 times the size of the original, each square surrounding the embedded shape will map to 10 squares of the duplicate’s perimeter. Once the perimeter of the duplicate is established, the grains outside it can disconnect from their neighbors.
The same algorithm can be varied to produce multiple, similarly sized copies of a sample shape, or to produce a single, large copy of a large object. “Say the tire rod in your car has sheared,” Gilpin says. “You could duct tape it back together, put it into your system and get a new one.” The cubes — or “smart pebbles” — that Gilpin and Rus built to test their algorithm enact the simplified, two-dimensional version of the system. Four faces of each cube are studded with so-called electropermanent magnets, materials that can be magnetized or demagnetized with a single electric pulse. Unlike permanent magnets, they can be turned on and off; unlike electromagnets, they don’t require a constant current to maintain their magnetism. The pebbles use the magnets not only to connect to each other but also to communicate and to share power. Each pebble also has a tiny microprocessor, which can store just 32 kilobytes of program code and has only two kilobytes of working memory. The pebbles have magnets on only four faces, Gilpin explains, because, with the addition of the microprocessor and circuitry to regulate power, “there just wasn’t room for two more magnets.” But Gilpin and Rus performed computer simulations showing that their algorithm would work with a three-dimensional block of cubes, too, by treating each layer of the block as its own two-dimensional grid. The cubes discarded from the final shape would simply disconnect from the cubes above and below them as well as those next to them.
True smart sand, of course, would require grains much smaller than 10-millimeter cubes. But according to Robert Wood, an associate professor of electrical engineering at Harvard University, that’s not an insurmountable obstacle. “Take the core functionalities of their pebbles,” says Wood, who directs Harvard’s Microrobotics Laboratory. “They have the ability to latch onto their neighbors; they have the ability to talk to their neighbors; they have the ability to do some computation. Those are all things that are certainly feasible to think about doing in smaller packages. It would take quite a lot of engineering to do that, of course,” Wood cautions. “That’s a well-posed but very difficult set of engineering challenges that they could continue to address in the future.”