The current communication fault diagnosis methods mainly focus on the classifier with fault probability, which often leads to the low diagnosis efficiency. In order to overcome the above problems, mobile robot communication fault diagnosis method based on swarm intelligence algorithm is proposed in the paper. Firstly, the abnormal data is extracted after the analysis of the communication data with Kalman filter. Secondly, the supporting decision model was designed to standardize the communication exchange process and locate the fault range. Futher more, the ant colony optimization algorithm combined with particle swarm optimization was used to locate the fault area, and the multi-model hybrid method was adopted to comprehensively judge the communication fault. The different interference ratio was used in the experiment to test the performance of the proposed algorithm compared with the SVM and Bayesian model. Finally, the experiment results show the validity of mobile robort communication fault diagnosis based on swarm intelligence algorithm.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.