Could the Future of Transportation for Some Cities Be Autonomous Boats?

Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and its Department of Urban Studies and Planning (DUSP) have announced they have developed a fleet of 3-D-printed autonomous boats designed to help alleviate traffic and ferry goods around cities, all while delivering "high maneuverability and precise control" thanks to improved algorithms.

Researchers say they see the boats transporting people during the day or during peak traffic hours, then using them for freight or other goods during off-hours or at night. "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," commented CSAIL Director Daniela Rus, co-author of a paper released last week describing the technology.

The boats -- rectangular in shape -- were originally designed as part of the "Roboat" project, a 2016 collaboration between the Amsterdam Institute for Advanced Metropolitan Solutions (AMS) and the MIT Senseable City Lab. This iteration improves on that project by adding "advance trajectory-tracking algorithms," improved precision docking techniques and rapid (and low-cost) fabrication via 3-D printing, among others.

The team used a nonlinear model predictive control (NMPC) algorithm to allow the boats to track their movements. "The NMPC and similar algorithms have been used to control autonomous boats before," MIT news commented in its announcement of the project. "But typically those algorithms 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 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 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."

The boats' hardware include GPS, microcontroller, an ultrasound-based positioning system and "outdoor real-time kinematic GPS modules, which allow for centimeter-level localization," MIT said.

Because the boats are modular, in the future researchers envision them being able to come together to build alternative structures such as, say, a musical stage or floating farmers market, and then break apart and go back to transporting people and goods after. "Some of the activities that are usually taking place on land, and that cause disturbance in how the city moves," Rus explained, "can be done on a temporary basis on the water."

A video of the boats in action can be found here.

About the Author

Becky Nagel is the former editorial director and director of Web for 1105 Media's Converge 360 group, and she now serves as vice president of AI for company, specializing in developing media, events and training for companies around AI and generative AI technology. She's the author of "ChatGPT Prompt 101 Guide for Business Users" and other popular AI resources with a real-world business perspective. She regularly speaks, writes and develops content around AI, generative AI and other business tech. Find her on X/Twitter @beckynagel.