Mobile robot pollution source identification based on statistics

In the source-finding algorithm based on information entropy, most of them do not consider the influence of obstacles. However, due to the obstruction of obstacles, gas will accumulate in front of it and lead to the emergence of pseudo-sources, which will interfere with the judgment of mobile robots. In order to improve the accuracy of source localization, a source identification method based on statistics is first adopted. Secondly, the Bug algorithm is combined with the source localization method to improve the confirmation region boundary of the algorithm, so that the robot can also identify the pseudo-source in the scene of large obstacles, thereby improving the source localization accuracy and making the source localization method more suitable for real scenes. By setting two scenarios on the MATLAB simulation platform, the judgment threshold is set and tested in two groups of simulations. The results show that the method is effective for the discrimination of pseudo-sources, and the robot can collect more concentration information, thereby improving the source positioning accuracy.