Abstract:
본발명은신뢰도기반자동인식장치설정방법및 신뢰도기반자동인식데이터보정방법에관한것이다. 본발명에따르면 AIDC 시스템의신뢰도를향상시키기위한자동인식장치의최적화된보정조건을자동으로설정하고자동인식장치가방사하는전파의최적화된출력파워를자동으로설정할수 있다. 따라서 AIDC 시스템의신뢰도를향상시키고 AIDC 시스템이수행되는환경의변화에용이하게대응할수 있다.
Abstract:
PURPOSE: A palette auto-feeding system is provided to automatically feed a palette to a workstation by sensing the load and presence of the palette through a sensor on the workstation. CONSTITUTION: A palette auto-feeding system comprises a palette rack(110), a first sensor(120a), a second sensor(120b), a moving unit(130), readers(160a,160b) and a system control unit(140). The palette rack holds the palette. The first sensor is installed on the palette rack and generates a first electrical signal, which corresponds to the load of the palette, which has been held on the palette rack. The second sensor generates a second electrical signal, which corresponds to the presence/absence of the palette on a workstation and the load of a cargo on the palette. The moving unit moves the palette from the palette rack to the workstation. The readers are attached to the palette.
Abstract:
An auto-recognition data correcting apparatus based on reliability, a method thereof, and a computer readable recording medium for recording a program for implementing the same are provided to generate data consistent with real data by correcting auto-recognition data even when application environment is inferior. A reliability based auto recognition data correcting apparatus comprises a data storage control unit(110), a data correction condition setting unit(140), and a data correction unit(170). The data storage control unit sets a data storage space for cumulative record of auto recognition data obtained in correspondence to an object from a data auto recognition apparatus. The data correction condition setting unit sets a correction condition as a reference for converting the auto recognition data for the object into correction data for the object based on pre-designated reliability. The data correction unit generates the correction data by comparing a cumulative record state of the auto recognition data with the correction condition.