After a 40-day, 3500-mile (5600km) journey from Plymouth, UK, The Mayflower Autonomous Ship (MAS) arrived in Halifax, Nova Scotia on Sunday 5th June. Throughout the voyage the ship’s ‘AI Captain’ guided the vessel using precise motion data from two Silicon Sensing AMU30 inertial measurement units (IMUs). These IMU’s also helped measure sea surface height as part of detailed scientific analysis of ocean topography.
Steve Capers, General Manager of Silicon Sensing Systems comments: “This is an incredible achievement. The Mayflower is the largest unmanned vessel to successfully make this difficult crossing. We congratulate everyone on this dedicated and hardworking team, and we are very proud of the contribution made by our small, rugged IMUs.”
The AMU30 is a micro electro-mechanical system (MEMS) unit with impressive inertial performance, including exceptional bias stability and low noise characteristics, plus an embedded Kalman Filter based AHRS (attitude and heading reference system) algorithm. It delivers precise 3-axis outputs of angular rate and acceleration, plus roll, pitch and heading angles, altitude and pressure, and temperature, at 200Hz – all critical to precise maritime navigation.
Two AMU30s made real-time, precision measurements of the movement of the Mayflower Autonomous Ship in 6 degrees of freedom (DOF) allowing the AI Captain to make minute manoeuvring adjustments to optimise vessel performance in a complex wavefield. They also provided redundant general navigation capability at sea.
When coupled with optical and RTK (real time kinematics) GPS information, they also assisted the ship in making highly accurate measurements of sea surface height, helping in the study of ocean tides, circulation and the amount of heat the ocean holds.
The MAS journey across the Atlantic retraced the voyage of the original Mayflower some 400 years ago. It is just one element of an extensive scientific data gathering and research programme the vessel will complete in the coming years. The ship is guided by its AI Captain, built using IBM cloud, artificial intelligence (AI) and edge computing technologies, and uses a hybrid engine that draws on solar power. Working with scientists and other autonomous vessels it provides a flexible platform for deepening understanding of issues such as climate change, ocean plastic pollution and marine mammal conservation. In parallel, the development of marine autonomous systems such as this will transform ocean-related industries such as shipping, oil & gas, telecommunications, security & defence, fishing & aquaculture.