Marine Research Platform

The marine research platform project is partly funded by the European Regional Development Fund. The goal is to develop an autonomous mobile marine research platform, using wind and solar energy. This is a resource efficient future option for different types of marine research. The aim is to further develop Åland Islands’ competency and innovation regarding unmanned and autonomous shipping and green technology.

The three year project is running through 2016-2018. The platform will be evaluated for marine sensor measurements and harbor porpoise monitoring in the Baltic Sea. In addition to Åland University of Applied Sciences, it involves marine research expertise and private companies.

For the marine sensor measurements we are cooperating with Husö Biological Station/ Åbo Akademi University. Regarding harbor porpoise monitoring the involved expert is Holger Klinck, bioacoustics researcher at Cornell University.

For the ASPire (Autonomous Sailing Platform) we will use a hull from a 2.4mR class sailboat, similar to the boat we have been sailing with previously. The rig consists of a free rotating wingsail built by Svenska Flygfabriken. This is an energy efficient solution that enables simple control and adjustment of the thrust force depending on the wind strength. The wind vane self steering device developed previously will be mounted on the boat, to enable energy efficient rudder control. Integration of electric propulsion will also be evaluated as a complement for windless conditions.

A 12 V system provides energy for sensors, microprocessors and actuators. This is charged by a solar panel tracking the position of the sun, developed by Heliozenit. The platform should be self-sufficient energy wise to be able to operate around the clock during the summer half-year.

The autonomous surface vehicle is equipped with a class B AIS transponder to allow for information exchange with other ships with AIS. In addition, a thermal imaging camera is mounted on the boat for collision avoidance purposes. Information from the AIS and the thermal imager are used for autonomous route adjustments due to obstacles.

For the control of the vehicle, a GPS sensor, a tilt-compensated magnetic compass sensor and an ultrasonic wind sensor are used. The control of the boat is handled by a Raspberry Pi computer connected to a CAN bus. On the CAN bus the wind sensor, AIS, wind vane position encoder, actuation control and solar panel movement are additional nodes.