학술논문

Extended Kalman Filter (EKF) Based Localization Algorithms for Mobile Robots Utilizing Vision and Odometry
Document Type
Conference
Source
2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON) Electrotechnical Conference (MELECON), 2022 IEEE 21st Mediterranean. :91-96 Jun, 2022
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Service robots
Navigation
Robot vision systems
QR codes
Cameras
Robot localization
Sensors
Data fusion
Sensor fusion
Laser range finder
Localization
Omni-camera
Sonar
Extended Kalman filter
GPS
Language
ISSN
2158-8481
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.