Evaluation of terrain collision risks for flight style autonomous underwater vehicles

Photographic surveys of the seafloor with flight style autonomous underwater vehicles are a very effective tool for discovery and exploration. Due to the high terrain collision risk for the survey vehicle, they are employed with caution. The extent of this risk remains unquantified. For mission planning, researchers and vehicle operators have to rely on their experience. This paper introduces measures for vehicle risk and success and analyses how previously mapped terrains and artificially generated terrain maps can be used to categorize terrains. The developed measures are applied to a simulation of the Autosub6000 flight style AUV terrain following system. Based on quantitative parameters, changes to the obstacle avoidance system and survey mission plans can be better informed

Adaptive probabilistic tack manoeuvre decision for sailing vessels

To move upwind, sailing vessels have to cross the wind by tacking. During this manoeuvre distance made good may be lost and especially smaller vessels may struggle to complete a tack in averse wind and wave conditions. A decision for the best tack manoeuvre needs to be made based on weather and available tack implementations.This paper develops an adaptive probabilistic tack manoeuvre decision method. The order of attempting different tacking strategies is based on previous success within a timeout, combined with an exploration component. This method is successfully demonstrated on the1m long sailing vessel Black Python. Four strategies for crossing the wind were evaluated through adaptive probabilistic choices, and the best was identified without detailed sensory knowledge of the actual weather conditions.Based on the positive results, further improvements for a better selection process are suggested and the potential of using the collected data to recognise the impact of weather conditions on tacking efforts is recognised