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.

定位，即在给定环境中估计一个人的位置是许多有人和无人移动系统的关键要素。由于对自主探索、巡逻和检查服务的高需求以及电池、传感器和机器学习算法的快速改进，定位质量对于智能机器人系统变得更加重要。由于水会在短距离内阻挡大部分信号，因此水下域是​​一个非常具有挑战性的环境。水下航行器定位技术的最新成果总结为两大类：被动技术，根据传感器的过去和当前信息，努力提供对航行器位置（全球或本地）的最佳估计，以及主动技术，