New Approach to Supervise Localization Algorithms

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

Fabrício de Oliveira Coelho (Author) Other; Pedro Miguel Guedes (Author) Other; Diana Alves Guimarães (Author) Other; Héber Miguel Sobreira (Author) Other; António Paulo Moreira (Author) FEUP

Conference proceedings International

Title: 2019 19TH IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC 2019)

Pages: 149-155

19th IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

Gondomar, PORTUGAL, APR 24-26, 2019

Indexing

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Other information

Authenticus ID: P-00Q-TAB

DOI: 10.1109/icarsc.2019.8733650

Abstract (EN): The localization algorithms have different errors which can impair the robot's navigation. In this way, we propose an approach that will supervise the localization while the robot navigate. Our approach is based on another work present in the literature, where we detected a problem during its analysis. Therefore, this article will present a new method based on the RLS algorithm, to solve the identified problem. Besides, we propose the supervision of two more localization algorithms, being now four the supervised algorithms, namely: Augmented Monte Carlo Localization, Extended Kalman Filter with Beacons, Perfect Match and Odometry. The results show that the robustness and reliability of the system were increased.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7