Speeding-up Particle Convergence with Probabilistic Active Localisation for AUV

An Autonomous Underwater Vehicle (AUV) needs to demonstrate a number of capabilities, in order to carry on autonomous missions with success. One of the key areas is autonomous localisation, i.e. the capability of the AUV to estimate correctly its position and orientation in the environment. However, most of the proposed approaches are “passive”, with no robot motion control involved. The “active” localisation incorporates the control of the robot motion, as a way to improve the robustness of the AUV localisation, finding the best path to follow in order to reduce the uncertainty in the state estimation. Representing the vehicle's belief of the state with particles, the active localisation module is triggered when there is a clear grouping in the particles and produces in output the path to be followed in order to drop the uncertainty. Both results on simulated data and tank trials have shown the advantages of using this technique compared to the classical ones.