Autonomous Boats and the Roboat Revolution

(MIT) – The future of transportation in waterway-rich cities such as Amsterdam, Bangkok, and Venice — where canals run alongside and under bustling streets and bridges — may one day make room for autonomous boats that ferry goods and people. These driverless boats might be adapted to perform city services overnight, instead of during busy daylight hours, further reducing congestion on both roads and canals.  Or, the boats — equipped with sensors, microcontrollers, GPS modules, and other hardware — could be programmed to self-assemble into floating bridges, concert stages, platforms for food markets, and other structures in a matter of hours. Perhaps the boats might have environmental sensors to monitor a city’s waters and gain insight into urban and human health.


Better design and control

The development of autonomous boats was conducted as part of the “Roboat” project, a collaboration between the MIT Senseable City Lab and the Amsterdam Institute for Advanced Metropolitan Solutions (AMS). Researchers are testing prototypes that cruise around city canals, moving forward, backward, and laterally along a preprogrammed path. Their recent work includes several new innovations: a rapid fabrication technique, a more efficient and agile design, and advanced trajectory-tracking algorithms that improve control, precision docking and latching, and other tasks.

To make the boats, the researchers 3-D-printed a rectangular hull with a commercial printer, producing 16 separate sections that were spliced together.   The completed hull was then sealed by adhering several layers of fiberglass. Integrated onto the hull are a power supply, Wi-Fi antenna, GPS, and a minicomputer and microcontroller. For precise positioning, the researchers incorporated an indoor ultrasound beacon system and outdoor real-time kinematic GPS modules, which allow for centimeter-level localization, as well as an inertial measurement unit (IMU) module that monitors the boat’s yaw and angular velocity, among other metrics. The boat is rectangular shaped, instead of the traditional kayak or catamaran shapes, which allows the vessel to move sideways and to attach itself to other boats when assembling into other structures. Another simple yet effective design element was thruster placement. Four thrusters are positioned in the center of each side, instead of at the four corners, generating forward and backward forces. This makes the boat more agile and efficient.

The team also developed a method that enables the boat to track its position and orientation more quickly and accurately. To do so, they developed an efficient version of a nonlinear model predictive control (NMPC) algorithm, generally used to control and navigate robots within various constraints. These NMPC algorithms have been used to control autonomous boats before, but typically, they are tested only in simulation or don’t account for the dynamics of the boat. The researchers instead incorporated in the algorithm simplified nonlinear mathematical models that account for a few known parameters, such as drag of the boat, centrifugal and Coriolis forces, and added mass in accelerating or decelerating water. The researchers also used an identification algorithm that identifies unknown parameters along the boat trained path. Finally, the researchers used an efficient predictive-control platform to run their algorithm, which can rapidly determine upcoming actions and increases the algorithm’s speed by two orders of magnitude over similar systems. While other algorithms execute in about 100 milliseconds, the researchers’ algorithm takes less than 1 millisecond.


Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Senseable City Lab have designed a fleet of autonomous boats that offer high maneuverability and precise control.

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Senseable City Lab have designed a fleet of autonomous boats that offer high maneuverability and precise control.


Testing the waters

To demonstrate the control algorithm’s efficacy, the researchers deployed a smaller prototype of the boat along preplanned paths in a swimming pool and in the Charles River. Over the course of 10 test runs, the researchers observed average tracking errors — in positioning and orientation — and have made corrections that dramatically improved performance. Indeed, navigation accuracy was integrated with  the boat’s onboard GPS and IMU modules, which helped improve identification of position and direction  down to the centimeter. The NMPC algorithm crunches the data from these onboard modules and considers several other metrics to steer the boat true. The algorithm is implemented in a controller computer and regulates each thruster individually, updating every 0.2 seconds. Significantly, the “controller” has essentially replaced the role of the boat-captain, capable of autonomously considering the boat’s dynamics, thrust constraints, and reference positions several seconds in advance, all of which optimizes how the boat drives on the path. The controller can also find optimal force for the thrusters that takes the boat back to its intended path and minimizes errors.

The innovations in design and fabrication as well as faster and more precise control algorithms have made the prospect of autonomous, driverless boats feasible, capable of being used for transportation, docking, and self-assembling into platforms. “Having swarms of robots in the canals of Amsterdam is a great idea,” says Javier Alonso-Mora, an assistant professor in the Cognitive Robotics Department at Delft University of Technology in the Netherlands. “Twenty percent of the surface in the Netherlands is water, and robots can be an efficient mode of transportation and logistics. This is a first step in that direction, with a very nice prototype that is able to move in all directions and connect with other boats to build temporal structures. Together with the team at MIT we are now looking at the next steps in autonomy, including multirobot coordination and urban navigation.” A next step for the work is developing adaptive controllers to account for changes in mass and drag of the boat when transporting people and goods. The researchers are also refining the controller to account for wave disturbances and stronger currents. “We actually found that the Charles River has much more current than in the canals in Amsterdam,” Mora says. “But there will be a lot of boats moving around, and big boats will bring big currents, so we still have to consider this.”


Adapted by AES editors from: Fleet of autonomous boats could service some cities, reducing road traffic. The full article was originally published here at MIT News.

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