EKF and computer vision for mobile robot localization

• Type: Article in International Conference Proceedings Book
• Date: 2018

Authors

Coelho, FO (Author) Other; Carvalho, JP (Author) FEUP; Pinto, MF (Author) Other; Marcato, AL (Author) Other

Conference proceedings International

Title: Proceedings of the 2018 13th APCA International Conference on Control and Soft Computing (CONTROLO)

Pages: 148-153

Indexing

Scopus - 7 Citations

Other information

Authenticus ID: P-00Q-2J2

DOI: 10.1109/controlo.2018.8514177

Abstract (EN): The autonomous robotic system accurate localization is a challenging step in robot navigation field once the mobile device should avoid dangerous situations, such as unsafe conditions and collisions. In this context, the present paper proposes a localization method using the Extended Kalman Filter (EKF) to fuse the information coming from two different sensors (i.e. odometry and computer vision). The localization results present with known and unknown starting points and are tested in a simulated environment. © 2018 IEEE.

Language: English

Type (Professor's evaluation): Scientific