Abstract
Localisation, i.e. estimation of one’s position in a given environment is a crucial element of many mobile systems, manned and unmanned. Due to the high demand for autonomous exploration, patrolling and inspection services and a rapid improvement of batteries, sensors and machine learning algorithms, the quality of localisation becomes even more important for smart robotic systems. The underwater domain is a very challenging environment due to the water blocking most of the signals over short distances. Recent results in localisation techniques for underwater vehicles are summarised in two principal categories: passive techniques, which strive to provide the best estimation of the vehicle’s position (global or local) given the past and current information from sensors, and active techniques, which additionally produce guidance output that is expected to minimise the uncertainty of estimated position.
Highlights
The field of underwater robotics has significantly grown in the last decades
Kondo and Ura analysed the difficulties for an Autonomous Underwater Vehicles (AUVs) of correctly localising itself in presence of strong magnetic disturbances, which are typical near steel underwater structures, or in presence of a particular geological configuration Kondo and Ura (2002)
The process is to use an a priori 3D-surface model of the permanent structure being navigated with the light model to generate artificial images which are compared against the real camera image to localise the AUV
Summary
The field of underwater robotics has significantly grown in the last decades. Nowadays Remotely Operated Vehicles (ROVs) are safely and routinely used, for example in the offshore industry, and Autonomous Underwater Vehicles (AUVs) are more and more used. The authors mean without the vehicle control in the loop It signifies that the robot tries its best to estimate its state, given the sensing history and the command history. The adjectives are referred to devices placed in the environment to facilitate the task of localisation According to those authors, a passive localisation approach deals with passive devices - for example a cat’s eye acoustic buoy (a device which reflects tuned sonar signals at specific frequencies depending on their composition, so to be more detected Smith and Williams 2005; Canning 2008), whilst an active localisation approach deals with active devices - for example an acoustic pinger, which actively sends an acoustic wave. The closing section will summarise the main techniques, present the shortfalls of the main approaches and outline the open questions addressed in this review
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