Robust Filter Development to Pursue Robotic Localization and Mapping Problem - Hamzah, Ahmad; Namerikawa, Toru (2011)
This paper deals with the development of a robust filter known as H Filter , as an approach to provide alternative solutions in robotic localization and mapping problem. In this problem, normally the environment conditions and noise characteristics are unknown which makes the Kalman Filter approach suffers. H Filter is proposed due its advantage in estimating conditions in non-Gaussian noise which Kalman Filter cannot offer. The analysis is shown by comparing the performance between H infinity Filter and Extended Kalman Filter for the above problem. Based on the simulation analysis and preliminary experiments, there is a high reliability in estimation of H Filter compared to Extended Kalman Filter regarding the robot location and landmark positions. Hence, H Filter can provide better solution especially in specific environment conditions with unknown noise characteristics.