Robust self-localization of mobile robots based on Kalman filter in dynamically changing environment

摘要

A mobile robot can identify its own position relative to landmarks, the locations of which are known in advance. The main contribution of this research is that it gives various ways of making the self-localizing error smaller by referring to a sensitivity which is defined as the ratio of the localizing error to sensor error. In this paper, the authors propose the index to evaluate the accuracy of the self-localizing methods. And then, a rational way to minimize the localizing error is proposed. Finally, we discuss a method to reduce the computational cost of selecting the best self-localizing method.