MIT researchers have taken significant steps toward creating robots that could virtually and economically assemble almost anything, including things much larger than themselves, from vehicles to buildings to larger robots.
The new work, from MIT’s Center for Bits and Atoms (CBA), builds on years of research, including recent studies showing that objects such as a deformable airplane wing and a functional racing car could be assembled from of tiny identical light pieces, and this robot. devices could be built to perform some of these assembly jobs. Now, the team has shown that both the assembly robots and the components of the structure being built can be made of the same subunits, and the robots can move independently in large numbers to achieve large-scale assemblies quickly
The new work is reported in the journal Nature Communications Engineering, in a paper by PhD student Amira Abdel-Rahman, ABC professor and director Neil Gershenfeld and three others.
A fully autonomous self-replicating robot assembly system capable of assembling larger structures, including larger robots, and planning the best construction sequence is still years away, Gershenfeld says. But the new work makes important advances toward that goal, including working out the complex tasks of when to build more robots and how big to make them, as well as how to organize swarms of robots of different sizes to build a structure efficiently without bump into another.
As in previous experiments, the new system involves large, usable structures built from an array of tiny identical subunits called voxels (the volumetric equivalent of a 2-D pixel). But while earlier voxels were purely mechanical structural pieces, the team has now developed complex voxels that can carry both power and data from one unit to another. This could enable the construction of structures that can not only support loads, but also perform work, such as lifting, moving and manipulating materials, including the voxels themselves.
“When we’re building these structures, you have to build intelligence,” says Gershenfeld. While earlier versions of the assembly robots were connected by bundles of cables to their power supply and control systems, “what emerged was the idea of structural electronics: making voxels that transmit power and data, as well as strength.” Looking at the new system in action, he notes, “There are no wires. There’s just the structure.”
The robots themselves consist of a chain of several voxels joined end to end. These can grab another voxel using attachment points at one end, then move like inches to the desired position, where the voxel can be attached to and released from the growing structure.
Gershenfeld explains that while the previous system demonstrated by members of his group could in principle build arbitrarily large structures, as the size of those structures reached a certain point relative to the size of the assembly robot, the process would become increasingly inefficient due to the longer and longer paths each bot would have to travel to get each piece to its destination. At that point, with the new system, the robots might decide it was time to build a larger version of themselves that could reach longer distances and reduce travel time. An even larger structure may require another such step, with new larger robots creating larger ones, while parts of a structure that include a lot of detail may require more smaller robots.
As these robotic devices work to assemble something, Abdel-Rahman says, they face choices every step of the way: “I could build a structure, or I could build another robot of the same size, or I could build a robot bigger.” Part of the work the researchers have focused on is creating the algorithms for this decision-making.
“For example, if you want to build a cone or a half-sphere,” he says, “how do you start the path planning and how do you break that shape up” into different areas that different bots can work on? The software they developed allows someone to input a shape and get an output that shows where to place the first block, and each block after that, based on the distances to travel.
There are thousands of published papers on path planning for robots, Gershenfeld says. “But the step after that, that the robot has to make a decision to build another robot or another kind of robot, that’s new. There’s really nothing before that.”
While the experimental system can carry out assembly and includes power and data links, in current versions the connectors between the small subunits are not strong enough to support the necessary loads. The team, including graduate student Miana Smith, is now focusing on developing stronger connectors. “These robots can walk and they can place parts,” says Gershenfeld, “but we’re almost, but not quite, at the point where one of these robots makes another one and goes away. And that’s because to the fit of things, like the strength of the actuators and the strength of the joints. … But it’s far enough that those are the parts that will drive it.”
Ultimately, these systems could be used to build a wide variety of large, high-value structures. For example, the way airplanes are currently built involves huge factories with gantry far larger than the components they build, and then “when you make a jumbo jet, you need jumbo jets to carry the jumbo jet parts to make it” , Gershenfeld. he says With a system like this built from small components assembled by small robots, “The final assembly of the aircraft is the only assembly.”
Similarly, when producing a new car, “you can spend a year tooling” before the first car is actually built, he says. The new system would avoid this whole process. These potential efficiencies are why Gershenfeld and his students have been working closely with car companies, airlines and NASA. But even the relatively low-tech building construction industry could also benefit.
While there has been a growing interest in 3D printed homes, these days these require printing machinery as large or larger than the home being built. Again, the potential for these structures to be assembled by swarms of small robots could provide benefits. And the Defense Advanced Research Projects Agency is also interested in the work because of the possibility of building coastal protection structures against erosion and sea level rise.
Aaron Becker, an associate professor of electrical and computer engineering at the University of Houston, who was not associated with this research, calls the paper “a home run… [offering] an innovative hardware system, a new way of thinking about scaling a swarm, and rigorous algorithms.”
Becker adds, “This paper examines a critical area of reconfigurable systems: how to quickly scale up a robotic workforce and use it to efficiently assemble materials into a desired structure. … This is the first work I’ve seen that attacks the problem from a radically new perspective: using a raw set of robot parts to build a set of robots whose sizes are optimized to build the desired structure (and other robots) as quickly as possible.”
The research team also included MIT-CBA student Benjamin Jenett and Christopher Cameron, who is now at the US Army Research Laboratory. The work was supported by NASA, US Army Research Laboratory and CBA consortium funding.