TY - JOUR
T1 - Real-Time Localization Scoring for Challenging Industrial Environments
T2 - Practical Experiments With Bluepath Robotics
AU - Yilmaz, Abdurrahman
AU - Dumandag, Umut
AU - Sari, Aydin Cagatay
AU - Savci, Ismail Hakki
AU - Temeltas, Hakan
N1 - Publisher Copyright:
© 1994-2011 IEEE.
PY - 2025
Y1 - 2025
N2 - Autonomous mobile robots (AMRs) are revolutionizing industries by enhancing flexibility and efficiency, particularly in dynamic environments, such as automotive manufacturing. These environments pose challenges due to their constantly changing layouts, unpredictable obstacles, and varying conditions, which impact the performance of localization systems. This article presents a novel real-time localization scoring architecture to address these challenges by quantifying the confidence in a robot’s positioning system. The proposed localization score improves map reconciliation, manages sensor interference, adapts navigation strategies, and enhances traffic coordination. Extensive experimental studies, including real-world deployment in an operational automotive production factory, demonstrate the robustness, accuracy, and adaptability of the developed localization score algorithm. The results showcase its potential to significantly enhance the operational efficiency and reliability of AMRs in industrial settings.
AB - Autonomous mobile robots (AMRs) are revolutionizing industries by enhancing flexibility and efficiency, particularly in dynamic environments, such as automotive manufacturing. These environments pose challenges due to their constantly changing layouts, unpredictable obstacles, and varying conditions, which impact the performance of localization systems. This article presents a novel real-time localization scoring architecture to address these challenges by quantifying the confidence in a robot’s positioning system. The proposed localization score improves map reconciliation, manages sensor interference, adapts navigation strategies, and enhances traffic coordination. Extensive experimental studies, including real-world deployment in an operational automotive production factory, demonstrate the robustness, accuracy, and adaptability of the developed localization score algorithm. The results showcase its potential to significantly enhance the operational efficiency and reliability of AMRs in industrial settings.
UR - https://www.scopus.com/pages/publications/105010888702
U2 - 10.1109/MRA.2025.3584350
DO - 10.1109/MRA.2025.3584350
M3 - Article
AN - SCOPUS:105010888702
SN - 1070-9932
JO - IEEE Robotics and Automation Magazine
JF - IEEE Robotics and Automation Magazine
ER -
