Sensor systems of industrial Autonomous Mobile Robots (ARM) constitute the main part of its information and measurement systems. The purpose of these systems is to form and provide information about the state of objects and processes in the environment and about the robot itself. This information is required for the functioning of the robot.

A sensitive device or a sensor is a primary transducer that reacts to the value to be detected (temperature, pressure, displacement, current, etc.) and converts it into another value, convenient for further use, giving a signal about its presence and intensity. This signal can be of any physical nature, determined by the principle of operation of the sensitive device. It is preferable that it is electrical, since most technical systems in which it will be used are electrical. However, there are systems of a different nature, for example, completely pneumatic, designed to work in conditions that do not allow electricity. In these cases, signals of a different nature must be used.

Requirements for sensor systems substantially depend on the level of the control system at which their information is used. Sensor systems used at control levels operating in real time should have the highest performance, with the inevitable simplification of this information. On the contrary, at the strategic level of controlling the behaviour of the robot, the most complete information is required, possibly to the detriment of performance.

Robotics is a complex and fascinating method for investigation of the surrounding space. A profound moment within the history of most robotics is that the expected value a robot performed a task below the influence of software package or electronics.

This work is devoted to the study of the possibilities of modernization and improvement of the navigation system of mobile robots in order to move in a space with obstacles. The research was carried out at the Industrial In-novation Arena in Skövde (Sweden).

The aim of the work is to develop the most sensitive sensor system of the robot to ensure easy movement in space with movable and fixed obstacles.

In this report, two methods will be used, the main method - Ullmans method and the evaluation method to select the optimal solution - Quality function deployment (QFD) method.

Based on the QFD, it was concluded that the most optimal is to use Simultaneous Localization and Mapping method (SLAM). For a more accurate result, further research in the laboratory will be required.