Sensor Fusion in Robot Localization using DS-Evidence Theory with Conflict Detection using Mahalanobis Distance

摘要

This article contains a new approach for combining sensory information for sensors with compatible information. Using Dempster-Shafer Evidence Theory, we show how to combine sensory information by Yager Combination rule. We also present a method to distinguish contrasts between Robots sensors outputs based on Mahalanobis distance, and find the sensor with irrelevant outputs. Experiments on a Robot facilitated with Vision and Encoder shows that this approach reduces localization error significantly, having better performance than Kalman Filter.