While self-driving cars have hogged the headlines for the past few years, other forms of autonomous transport are starting to heat up.
This month, IBM and Promare, a UK-based marine research and exploration charity, will trial a prototype of an artificial intelligence (AI)-powered maritime navigation system ahead of a September 16th venture to send a crewless ship across the Atlantic Ocean on the very same route the original Mayflower traversed 400 years ago.
The original Mayflower ship, which in 1620 carried the first English settlers to the U.S., traveled from Plymouth in the UK to what is today known as Plymouth, Massachusetts.
Mayflower version 1.0 was a square-rigged sail ship, like many merchant vessels of the era, and relied purely on wind and human navigation techniques to find its way to the New World. The Mayflower Autonomous Ship (MAS), on the other hand, will be propelled by a combination of solar- and wind-generated power, with a diesel generator on board as backup.
Moreover, while the first Mayflower traveled at a maximum speed of around 2.5 knots and took some two months to reach its destination, the upgraded version moves at a giddy 20 knots and should arrive in less than two weeks.
The mission, first announced back in October, aims to tackle all the usual obstacles that come with navigating a ship through treacherous waters, except without human intervention.
The onboard “AI Captain,” as it’s called, can’t always rely on GPS and satellite connectivity, and speed is integral to processing real-time data. This is why all the AI and navigational smarts must be available locally, making edge computing pivotal to the venture’s success.
“Edge computing is critical to making an autonomous ship like the Mayflower possible,” noted Rob High, IBM’s CTO for edge computing. “The ship needs to sense its environment, make smart decisions about the situation, and then act on these insights in the minimum amount of time — even in the presence of intermittent connectivity, and all while keeping data secure from cyberthreats.”
The team behind the new Mayflower has been training the ship’s AI models for the past few years, using millions of maritime images collected from cameras in the Plymouth Sound, in addition to other open source data sets.
For machine learning prowess, the ship is using an IBM Power AC922 system, which is used in some of the world’s biggest AI supercomputers. Alongside IBM’s PowerAI Vision, the Mayflower’s AI Captain is built to detect and identify ships and buoys — as well as other hazards, including debris — and to make decisions about what to do next.
For example, if the MAS encounters a cargo ship that has shed some of its load after colliding with another vessel, the AI Captain will be called into action and can use any combination of onboard sensors and software to circumvent the obstacles. The radar can detect hazards in the water ahead, with cameras providing additional visual data on objects in the water.
Moreover, an automatic identification system (AIS) can tap into specific information about any vessels ahead, including their class, weight, speed, cargo type, and so on. Radio broadcast warnings from the cargo ship can also be accepted and interpreted, with the AI Captain ready to decide on a change of course.
Other data the AI Captain can tap into includes the navigation system and nautical chart server, which provide the current location, speed, course, and route of the ship, as well as attitude sensors for monitoring the state of the sea and a fathometer for water depth.
The onboard vehicle management system also provides crucial data, such as the battery charge level and power consumption, that can be used to determine the best route around a hazardous patch of ocean, with weather forecasts informing the final decision.
Crucially, the AI Captain can communicate vocally with other ships in the vicinity to communicate any change in plans.
The MAS ship itself is still being constructed in Gdansk, Poland, and the AI Captain will be tested this month in a manned research ship called the Plymouth Quest, which is owned by the U.K.’s Plymouth Marine Laboratory.
The test will essentially determine how the AI Captain performs in real-world scenarios, and feedback will be used to refine the main vessel’s machine learning smarts before the September launch.