Grant: Discovery Grants Program - Individual

Autonomous underwater vehicles (AUVs) are playing an increasingly important role in ocean observations and sea floor mapping. In particular, autonomous underwater gliders have seen a dramatic increase in usage. Gliders move through the water column in a saw-tooth pattern. By changing their weight in water from positively to negatively buoyant they can reverse their direction of motion from upward to downward. A set of fixed wings generates, similar to a soaring plane, lift and drag that propel the vehicle not only in the vertical but also in the horizontal direction, generating the characteristic saw-tooth motion pattern. In this research I am proposing to develop algorithms and sensing solutions for gliders, that help them (a) to navigate more accurately while they are submerged and (b) will be able to estimate the water currents they are flying in. These objectives will be achieved by a developing a highly accurate mathematical model of the gliders' dynamics. One of the inputs into this model will be the external flow conditions. The output of the model will consist of position and attitude as well as the associated velocities. Since the physical gliders are instrumented with depth and attitude sensors these measurements potentially can be used to extract the unknown flow conditions using an inverse model. The extracted flow information is of great importance to physical oceanographers in itself but it also can be used to improve the navigation accuracy of the glider while submerged. The long-term objectives of this research program are to achieve long duration missions, potentially under the ice, without the need for frequent surfacings for position updates. Together with a to-be developed acoustic long-range underwater navigation system, the above described short-term goals will help to achieve this objective and will give access to areas that are permanently or seasonally ice-covered. This enabling technology will give scientists access to these regions and provide them with data previously unavailable.