Extended Kalman Filter Implementation for the Khepera II Mobile Robot

Authors

Thomas J. Otahal
Herbert G. Tanner

Document Type

Technical Report

Publication Date

1-21-2009

Abstract

The accurate estimation of robot position and orientation in real-time is one of the fundamental challenges in mobile robotics. The Extended Kalman Filter is a nonlinear real-time recursive time domain filter that combines available sensor data to produce an accurate estimate of state, and has been successfully applied to the localization problem in mobile robotics and aircraft navigation. This report describes an Extended Kalman Filter implementa- tion for the Khepera II mobile robotics platform that seeks to produce accurate localization estimates in real-time using wheel odometry data, IR sensor range data, and compass heading data.

Language (ISO)

English

Keywords

Mobile robots, localization

Recommended Citation

Otahal, Thomas J. and Herbert G. Tanner. "Extended Kalman Filter Implementation for the Khepera II Mobile Robot." (2009). https://digitalrepository.unm.edu/me_fsp/5