Uploaded April 2023 | Updated September 2026, 3 weeks ago
This video presents results on autonomous exploration and visual inspection of a ballast tank inside an FPSO vessel. Specifically, RMF – a collision tolerant aerial robot implementing multi-modal SLAM and path planning functionality – is deployed inside the ballasts of the vessel and performs the autonomous inspection of 3 tank compartments without any prior knowledge of the environment other than a rough estimate of the geometric midpoint of each compartment. Such information is readily available and does not require access to hard-to-access CAD models of ships. The mission takes place in less than 4 minutes and ensures both the geometric mapping of those compartments and their visual inspection with certain resolution guarantees.
In further detail, the process starts with the robot in the first compartment where it performs autonomous exploration to map it geometrically with its LiDAR. It then calculates a path to inspect all the mapped surfaces visually subject to a minimum resolution of observation. Upon completion of this process in one compartment, the method proceeds to the next compartment and the whole procedure is iteratively repeated. After geometrically exploring and visually inspecting a given number of compartments, the system autonomously returns to the deployment point.
This result is part of our effort to ensure semantics-aware autonomous missions that ensure first the exploration and then the detailed visual inspection of structures of interest inside ballast tanks and other key areas of maritime vessels or broadly industry facilities.
This video presents results on autonomous exploration and visual inspection of a ballast tank inside an FPSO vessel. Specifically, RMF – a collision tolerant aerial robot implementing multi-modal SLAM and path planning functionality – is deployed inside the ballasts of the vessel and performs the autonomous inspection of 3 tank compartments without any prior knowledge of the environment other than a rough estimate of the geometric midpoint of each compartment. Such information is readily available and does not require access to hard-to-access CAD models of ships. The mission takes place in less than 4 minutes and ensures both the geometric mapping of those compartments and their visual inspection with certain resolution guarantees.
In further detail, the process starts with the robot in the first compartment where it performs autonomous exploration to map it geometrically with its LiDAR. It then calculates a path to inspect all the mapped surfaces visually subject to a minimum resolution of observation. Upon completion of this process in one compartment, the method proceeds to the next compartment and the whole procedure is iteratively repeated. After geometrically exploring and visually inspecting a given number of compartments, the system autonomously returns to the deployment point.
This result is part of our effort to ensure semantics-aware autonomous missions that ensure first the exploration and then the detailed visual inspection of structures of interest inside ballast tanks and other key areas of maritime vessels or broadly industry facilities.
