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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. The boats can also be rapidly 3-D printed using a low-cost printer, making mass manufacturing more feasible. The boats could be used to taxi people around and to deliver goods, easing street traffic, or even perform city services overnight, instead of during busy daylight hours. Credits Courtesy of the researchers
A fleet of autonomous boats could someday reduce traffic in large cities, while also improving government services.
Researchers from the Massachusetts Institute of Technology’s (MIT) Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Senseable City Lab in the Department of Urban Studies and Planning (DUSP) have developed an autonomous boat that combines high maneuverability with precise control and can be rapidly printed using only a low-cost 3D printer.
The researchers believe that an easier mass manufacturing method for autonomous boats could ease congestion in high population centers to taxi people around and deliver goods. The researchers also believe driverless boats can be adapted to perform city services overnight to further reduce congestion.
“Imagine shifting some of infrastructure services that usually take place during the day on the road—deliveries, garbage management, waste management—to the middle of the night, on the water, using a fleet of autonomous boats,” CSAIL Director Daniela Rus, a co-author on the study, said in a statement.
To make the new boats, the researchers first 3D printed a rectangular hull with a commercial printer, producing 16 separate sections that were spliced together and sealed by adhering several layers of fiberglass.
They then integrated a power supply, Wi-Fi antenna, GPS and a minicomputer and microcontroller onto the hull. 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.
Rather than the traditional kayak or catamaran shapes, the boats are built in a rectangular shape that allows it to move sideways and attach itself to other boats when assembling other structures.
The researchers also used four thrusters that were positioned in the center of each side to generate forward and backward forces, making the boat more agile and efficient.
To improve the control of the boats, the team also developed a method that enables the boat to track its position and orientation more quickly and accurately with a more efficient version of a nonlinear model predictive control algorithm that is used to control and navigate robots within various constraints.
To improve the algorithm, the researchers incorporated simplified nonlinear mathematical models that account for a few known parameters like drag of the boat, centrifugal and Coriolis forces and added mass due to accelerating or decelerating in water. The researchers also used an identification algorithm that then identifies any unknown parameters as the boat is trained on a path.
The researchers finally used an efficient predictive-control platform to run the algorithm, which can rapidly determine upcoming actions and increase the algorithm’s speed by two orders of magnitude over similar systems at less than one millisecond.
To test the control algorithm, the researchers deployed a smaller prototype of the boat along preplanned paths in a swimming pool and in the Charles River. During 10 test runs, the researchers’ observed average tracking errors smaller than tracking errors of traditional control algorithm.
The work 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). In 2016, as part of the project, the researchers tested a prototype that cruised around the city’s canals, moving forward, backward, and laterally along a preprogrammed path.
The new boats can be programmed to self-assemble into floating bridges, concert stages, platforms for food markets and other structures in only a few hours.
“Again, some of the activities that are usually taking place on land, and that cause disturbance in how the city moves, can be done on a temporary basis on the water,” said Rus, who is the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science.
Another possibility is that the boats could be equipped with environmental sensors that can monitor a city’s waters and gain insight into urban and human health.
The researchers are now working to develop adaptive controllers to account for changes in mass and drag of the boat when transporting people and goods. They are also refining the controller to account for wave disturbances and stronger currents.
