We present a novel marine mapping system using an Autonomous Surface Craft (ASC). The platform includes an extensive sensor suite for mapping environments both above and below the water surface. A relatively small hull size and shallow draft permits operation in cluttered and shallow environments. We address the Simultaneous Mapping and Localization (SLAM) problem for concurrent mapping above and below the water in large scale marine environments.

Our key algorithmic contributions include:

  • Methods to account for degradation of GPS in close proximity to bridges or foliage canopies
  • Scalable systems for management of large volumes of sensor data to allow for consistent online mapping under limited physical memory.

Experimental results are presented to demonstrate the approach for mapping selected structures along the Charles River in Boston. This work was with Jacques Leedekerken.

Related Publication:

Note the huge scale difference between the Harvard Bridge and our kayak:

Robotic Kayak The huge scale difference between the Harvard Bridge and our kayak

MIT Pavilion and Harvard Bridge Reconstructions - different colours represent the different SLAM submaps:

MIT Pavilion Mesh Reconstruction A mesh reconstruction of the Harvard Bridge - different colours represent the different SLAM submaps

Left: A collapsed bridge in Malahide, Ireland - a motivation for this work. Right: the full area surveyed in this work: the Charles Basin, about 3km East-West:

A collapsed bridge in Malahide, Ireland - a motivation for this work The full area surveyed in this work: the Charles Basin, about 3km East-West

River Exploration with a Small Marine Vessel: We also explored the feasibility of point-to-point river navigation in regions such as the up-river environments where GPS is denied – a ‘DARPA Grand Challenge on water’.

As part of the project a fully sensor-equipped robotic vehicle was equipped with the following sensor suite:

  • BlueView MB2250 Microbathmetry Sonar
  • Garmin GMR18 Marine Radar
  • 2-3 SICK LIDAR Range Sensors
  • Two separate computers, with a total of 6 cores.

Sensor Enabled Kayak Kayak in the Charles near MIT