Most individuals consider the waterfront as the sting of town. A team of MIT researchers sees it as a dynamic, Lego-like construction site.
Their latest system, called “FloatForm,” is a swarm of small square robotic boats that assemble themselves into larger structures on the water, break apart, and reassemble into something latest, all with minimal human direction.
Each robot, in regards to the size of a dinner plate at 21 centimeters square, is a self-contained vessel with its own thrusters, sensors, and magnetic latches. Together, they hint at a future by which floating infrastructure could turn out to be more adaptive: a short lived platform after an emergency, a market on a canal, or a stage that appears for a festival and dissolves when the group goes home.
“Our FloatForm projects envisions a future where the waterfront becomes a programmable extension of town, where autonomous boats can self-organize into bridges, platforms, and other useful structures on demand,” says Daniela Rus, the Panasonic Professor of Electrical Engineering and Computer Science at MIT and director of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). “This sort of distributed robotics opens latest possibilities for mobility, emergency response, public space, and infrastructure on water.”
“With FloatForm, we’re essentially turning static water surfaces into dynamic, programmable spaces,” says Wei Wang, lead writer of a brand new paper on the project and a former MIT research scientist who now leads the Marine Robotics Lab on the University of Wisconsin at Madison. “Imagine an urban environment where public space isn’t fixed, but can autonomously expand, contract, or reconfigure on demand.”
“We see it as forming infrastructure on the water, using a modular system to create one larger system,” says Alejandro Gonzalez-Garcia, a former researcher with MIT CSAIL and the Senseable City Lab. “If there’s an emergency, you may form a brand new bridge to alleviate traffic in town. Or you may create floating markets and floating stages. For those who desire a more livable city, you ought to use the water, too.”
The open-access work, published today in Nature Communications, comes from the labs of Rus and Carlo Ratti, professor of practice of urban technologies and planning at MIT and director of the Senseable City Lab, and grows out of Roboat, their joint project with the Amsterdam Institute for Advanced Metropolitan Solutions that put full-size autonomous vessels on Amsterdam’s canals. Those canals once carried town’s goods; today, they mostly carry tourists.
“We explored whether the canals might be used for waste collection, or for transport, to dump a few of the stress on the roads back onto the water,” says Niklas Hagemann, an MIT graduate student in architecture, CSAIL affiliate, and former Senseable City Lab researcher who has worked on the project since its early stages. “Urban areas are getting denser, so could you expand public space onto water that’s currently underutilized?”
FloatForm shrinks that vision right down to tabletop scale to reply a harder query: How do you get dozens, and eventually hundreds, of floating robots to arrange themselves?
Lessons from the ant raft
The team found its answer in biology. Fire ants famously survive floods by linking their bodies into living rafts, with no leader choreographing the assembly. Each ant follows easy local rules, and a resilient structure emerges.
“Each ant is an independent agent,” says Gonzalez-Garcia. “We wanted each robot to have its own capabilities, the identical way ant colonies form a raft.”
Most existing self-assembling robot systems, on water and elsewhere, depend on a central computer dictating every move. That approach is vulnerable to single points of failure and scales poorly: The planning math balloons as robots are added, and the swarm must assemble sequentially, with most robots idling while they wait their turn. FloatForm flips the balance. A light-weight central planner steps in just sparingly, assigning each robot a final position to perfect the lattice, a level of geometric precision that purely distributed methods struggle to ensure. Every part else, including navigating toward the goal shape, avoiding collisions, and adapting to disturbances, runs on the robots themselves, which coordinate by exchanging positions with their immediate neighbors. The entire swarm moves directly.
That parallelism is what sets the work apart. The planning complexity of FloatForms approach depends only on a robot’s local neighbors, not the full size of the swarm. “What we’re attempting to do is to have minimal central intervention, and have all of them move together at the identical time,” says Gonzalez-Garcia.
In experiments at MIT, a fleet of eight robots repeatedly gathered from random positions right into a goal shape, latched right into a rigid structure, broke apart on command, reassembled right into a latest configuration, after which drove across the pool as a single vessel, with each run taking 4 to eight minutes. In that final mode, called collective transport, a planner charts a trajectory for the entire structure and every robot computes its own contribution. “Every robot becomes an actuator,” Gonzalez-Garcia explains. Simulations showed the framework scaling easily to swarms of 64.
“The fantastic thing about this largely decentralized approach is that the computation doesn’t get bogged down because the swarm grows,” says Wang. “Whether you’re working with eight boats or 80, your entire fleet coordinates and moves concurrently. Because the general assembly time doesn’t significantly increase in principle, the system stays highly scalable.”
There is a physical payoff to sticking together, too. “Our boats turn out to be more stable by joining together, just like the ant raft, if you could have waves or currents,” Hagemann says.
An origami handshake
The robots connect through a latching mechanism hidden entirely inside each hull. A single servo motor at the middle drives an origami-inspired auxetic structure, a geometry that contracts uniformly in all directions directly, pulling everlasting magnets on all 4 sides inward to release, or pushing them outward to grab a neighbor across gaps of 10 to fifteen centimeters. The magnets are arranged with alternating polarities, so the boats reliably click into clean square lattices.
The elegant part is what the mechanism doesn’t do: devour (much) power. A 3D-printed gearbox holds the latch in either state with the motor switched off. “It uses energy to latch and de-latch, but in between those states, it doesn’t use any energy,” says Hagemann. For infrastructure that may hold a configuration for hours, that matters. “Since the robots are so small, you possibly can only have a battery so big,” adds Gonzalez-Garcia. “In the event that they use less energy on latching, they’ll use more on computation, or on actually moving.”
Getting there took some humbling engineering. 4 miniature thrusters arranged in an “X” give each robot omnidirectional motion, including turning in place, but they pack large forces relative to the robots’ tiny inertia, which made early prototypes twitchy and susceptible to aggressive spins at low speeds. The team added stabilizing fins to extend hydrodynamic drag and tuned the controllers to remain robust across robots that, at this scale, are never quite an identical. The magnets posed their very own problem: They held on so well that de-latching sometimes required the robots to twist themselves free.
From the tank to the canal
Across 10 trials, the system accomplished its missions without human intervention 90 percent of the time with 4 robots and 70 percent with eight. When things did go fallacious, the architecture showed its resilience: A robot that briefly lost its bearings could rejoin the structure by itself, without bringing the entire swarm to a halt, and robots stuck in formation deadlocks learned to shake themselves free and retry.
Moving from a controlled indoor tank to an actual canal or harbor will take greater than confidence. “There’s all the time a relationship between the scale of a ship and the magnitude of the disturbance it may well handle,” says Gonzalez-Garcia. “These boats are very small, so in very disturbed water, they can’t work.” Scaling up will mean reinforcing the latches, potentially with mechanical interlocking just like the full-size Roboat used, and trading the lab’s ultrasonic indoor positioning for GPS or vision-based sensing. Helpfully, the coordination algorithm was designed to be sensor-agnostic: swap the sensors, keep the logic.
The team envisions applications well beyond city canals, from forming temporary platforms for offshore inspection and maintenance to adaptive sensor networks for studying migratory species to reconfigurable docking stations for emergency response in hard-to-reach areas. There may be also potential for offshore and distant operations, from temporary construction platforms to environmental monitoring and scientific expeditions.
And the geography is wide open. “Venice, the Netherlands, Belgium, the fjords and lakes of Norway, really any city with a river can make the most of this,” says Gonzalez-Garcia. “The project uses spaces where water is already necessary, however it also raises the query: Where else can water be used for something more?”
“That is an exciting step forward in realizing distributed collective behaviors on water,” says University of Michigan Assistant Professor Steven Ceron, who wasn’t involved within the research. “Assembly, self-reconfiguration, and collective motion are difficult enough in dry environments, but achieving these behaviors in a predominantly distributed fashion on water represents a serious additional challenge, and this team has credibly overcome it. By shifting the computational burden onto the robots themselves, they’ve built a more resilient system that within the near future could enable robot collectives like this to be deployed in open-water environments for search operations, environmental monitoring, and reconfigurable marine infrastructure.”
Gonzalez-Garcia, Hagemann, and Wang wrote the paper with senior authors Ratti, who can also be a professor at Politecnico di Milano, and Rus. Gonzalez-Garcia is moreover affiliated with the MECO Research Team at KU Leuven. The research was supported by a grant from the Amsterdam Institute for Advanced Metropolitan Solutions, with additional support from the University of Wisconsin at Madison. The team thanks MIT Sea Grant and Professor Michael Triantafyllou for providing the test tank.