Open AccessAn Accurate and Robust Flexible Guidance System for Indoor Industrial Environments
Author(s) -
David Herrero-Pérez,
Juan José Alcaraz-Jiménez,
Humberto Martínez Barberá
Publication year - 2013
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/56478
Subject(s) - computer science , robustness (evolution) , odometry , extended kalman filter , fuse (electrical) , kalman filter , industrial robot , real time computing , positioning system , simulation , artificial intelligence , point (geometry) , robot , mobile robot , engineering , biochemistry , chemistry , geometry , mathematics , electrical engineering , gene
This work presents the development of a flexible industrial guidance system used to guide Automated Guided Vehicles (AGVs) in indoor industrial environments. Typically, wireless guidance systems are composed of path‐tracking and localization methods linked to follow a certain route. This paper focuses on the localization approach that permits industrial vehicles to operate indoors with the grade of accuracy, repeatability and reliability required by industrial applications. A key point is that, apart from accuracy, the position estimates should be performed at a high sample rate in order to permit the path tracker to follow the route properly. Robustness of absolute positioning is also crucial in industrial applications. An Extended Kalman Filter (EKF) is adopted to fuse the information provided by a laser navigation system and odometry. The effectiveness of the development is tested using a custom modified commercial industrial vehicle operating in an industrial setting