Purpose: The paper is concerned about intelligent motion of the mobile robot in the production area. The robot is self-learning and gathers the data from the environment by means of sensors. It processes the acquired information and utilizes it for making decisions. Design/methodology/approach: The concept imitates the natural selection of living organisms, where in the struggle for natural resources the fit individuals become more and more dominant and adaptable to the environment in which they live, whereas the less fit ones are present in the generations rarely. Some of the improved genetic operations were used for the robot motion. Findings: The use of those improved genetic operations has proved to be appropriate. By means of them the robot became more and more intelligent in the course of evolution and performed the set task successfully. Research limitations/implications: The tests were limited only to the space with static barriers. In future, it would be appropriate to test the proposed system also in the space with moving objects and to enable the robot to have full autonomy. Practical implications: The proposed system enables the robot to move completly independently in the space. The robot complies with simple instructions: come to the goal fastest possible (shortest path) without causing damage to youself and to the environment. Originality/value: Originality value is the implementation of the non-deterministic principles in the decision making strategy of the mobile robot. In learning and independent decision making the robot used some of the improved genetic operations.