Autonomous underwater vehicles (AUVs) are robots that operate in underwater environment and do not need involvement of an operator when performing some tasks. In order to move independently in water environment, AUVs need navigation capabilities, on the one hand, they have to be able to detect obstacles and avoid them, and on the other hand, they also have to know their own position and spatial orientation, at least course. With regard to the orientation, there are many various solutions like inertial systems, inclinometers, magnetic compasses, optical gyro–compasses, whereas, position due to unavailability of GPS requires solutions dedicated to underwater environment such as inertial navigation. To this end, information about spatial orientation and velocity is necessary. When the vehicle is not equipped with a device to measure velocity, e.g. because of small size of the vehicle itself, the only solution is to use odometry, that is, to apply information from the drive to estimate the velocity. The paper presents Odometric Navigational System (ONS) designed for a small biomimetic autonomous underwater vehicle (BAUV) and tuned by means of neuro–evolutionary techniques. To verify system performance, data from the real BAUV were applied.

自主水下航行器（AUV）是在水下环境中运行的机器人，在执行某些任务时不需要操作员的参与。为了在水环境中独立移动，AUV需要导航功能，一方面，它们必须能够检测并避开障碍物，另一方面，它们还必须了解自己的位置和空间方向，例如：最少的课程。关于方向，有许多解决方案，例如惯性系统，测斜仪，磁罗经，光学陀螺罗盘，而由于GPS的不可用而导致的定位需要专门针对水下环境的解决方案，例如惯性导航。为此，需要有关空间方向和速度的信息。当车辆未配备测量速度的设备时，例如 由于车辆本身的体积小，唯一的解决方案是使用里程计，即应用来自驱动器的信息来估计速度。本文介绍了为小型仿生自主水下航行器（BAUV）设计的里程表导航系统（ONS），并通过神经进化技术对其进行了调整。为了验证系统性能，使用了来自实际BAUV的数据。