Litcius/Paper detail

Extended Kalman Filter (EKF) Based Localization Algorithms for Mobile Robots Utilizing Vision and Odometry

Hoang T. Tran, Thanh Vo, Trần Lê Thăng Đồng, Quan N.A. Nguyen, Duyen M. Ha, Quang N. Pham, Thanh Q. Le, Thang K. Nguyen, Hai T., Minh Tuấn Nguyễn

20222022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON)13 citationsDOI

Abstract

In this paper, we describe a positioning method for a moving mobile robot in a known environment. The proposed technique incorporates location estimation by letting cameras to recognize the QR code from fixed markers. These fixed points will provide the reference points listed in the database. The system will calculate the angle to each landmark and then correct the robot’s directions. The extended Kalman filter is deployed to correct the position and orientation of the robot from the error between the viewing angle and the estimate to each datum. The experimental results show that the approach improves and suffices in robot localization for navigation tasks. Results from experiments in real environments are presented including analysis. The results are significant and show promise.

Topics & Concepts

OdometryExtended Kalman filterComputer visionComputer scienceArtificial intelligenceKalman filterMobile robotLandmarkRobotOrientation (vector space)QuaternionPosition (finance)Visual odometryAlgorithmMathematicsEconomicsFinanceGeometryRobotics and Sensor-Based LocalizationRobotic Path Planning AlgorithmsIndoor and Outdoor Localization Technologies