This paper proposes a heading drift correction algorithm for inertial and positioning sensor fusion for indirect localization of industrial products in warehouse management. The tracking of objects is performed indirectly during their transportation by constantly tracked industrial machinery (e.g., forklift). The fusion of inertial and positioning units provide real-time information on position and heading of industrial machinery, which is transformed into real-time position of the carried payload. Within this work, a test setup was assembled and based on the proposed inertial measurement unit (IMU) heading correction algorithm. The performance of the solution was assessed in an industrial production environment. Results show that the proposed algorithm was able to reduce the heading median error from 44.1 degrees to 5.9 degrees, which is 86.5% improvement in measured heading accuracy. This results in an improvement of the positioning accuracy from 1.91 m median error to 0.26 m median error for the indirectly tracked object.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.