Posts Tagged ‘underwater’

November 9th, 2011

Underwater ROV keeps its eye on the target - article


Towards semi-autonomous operation of under-actuated underwater vehicles: sensor fusion, on-line identification and visual servo control
George C. Karras, Savvas G. Loizou, Kostas J. Kyriakopoulos

Underwater robots can be used to inspect water-bound structures such as ship hulls. Remote-operating these vehicles can be tricky if they are under-actuated, meaning you can’t fully control their motion. For example, you might command the robot to go forward but uncontrolled sway could result in the robot moving sideways. This can be challenging if you’re trying to inspect an object using a camera, and the object keeps slipping out of your field of view.

To solve this problem, Karras et al. propose a semi-autonomous control scheme that ensures the robot doesn’t lose sight of the inspection target. The control fuses information (using an asynchronous Modified Dual Unscented Kalman Filter) from sensors on the robot to estimate its position and attitude and correct its trajectory when needed.

Experiments were conducted in a test tank using an under-actuated underwater robot that uses only three thrusters. Information for sensor fusion is provided by an Inertial Measurement Unit (IMU), a camera, and two laser pointers which are parallel to the camera axis. By monitoring where the lasers point using the camera, the robot can figure out how it is moving with respect to the inspection target.

Results show the feasibility and applicability of the semi-autonomous control scheme. In the future, the authors hope to extend their approach to more difficult tasks such as inspecting fish farm nets.

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May 13th, 2011

Underwater 3D mapping - article


Spectral registration of noisy sonar data for underwater 3D mapping
Heiko Bülow, Andreas Birk

We saw the need for good underwater robots during the Deepwater spill last summer. In such scenarios, a remote operator controls a robot equipped with a camera and means to build a 2D map of the environment. However, if you want your robot to inspect non-trivial structures such as oil- and gas- production and transport equipment, or if you want it to be more autonomous in challenging environments, 3D mapping is essential.

As seen in previous posts, to make a 3D map for a ground robot you might use a laser-range finder. However, similar sensors are not available in underwater environments and the researchers are left coping with low-resolution and noisy measurement systems. To solve this problem, Bülow et al. propose a new method to combine sensory information from noisy 3D sonar scans that partially overlap. The general idea is that the robot scans the environment, moves a little, and then scans the environment again such that the scans overlap. By comparing them, the researchers are able to figure out how the robot moved and can use that to infer where each scan was taken from. This means that there is no need to add expensive motion sensors typically required by other state-of-the-art strategies (Inertial Navigation Systems, and Doppler Velocity Logs).

The approach was first tested in simulation on virtual images with controllable levels of noise. Results show that the method is not computationally expensive, can deal with large spatial distances between scans, and that it is very robust to noise. The authors then plunged a Tritech Eclipse sonar in a river in Germany to generate 18 scans of the Lesumer Sperrwerk, a river flood gate. Results from that experiment shown in the video below compared well to other approaches described in the literature.



In the future, Bülow et al. hope to combine this approach with SLAM to avoid the accumulation of relative localization errors.

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