Details

Autor(en) / Beteiligte

• Tran, Hoang T.
• Vo, Thanh C.
• Tran, Dong Lt
• Nguyen, Quan Na
• Ha, Duyen M.
• Pham, Quang N.
• Le, Thanh Q.
• Nguyen, Thang K.
• Do, Hai T.
• Nguyen, Minh T.

Titel

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

Ist Teil von

• 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON), 2022, p.91-96

Ort / Verlag

IEEE

Erscheinungsjahr

2022

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• 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.