Automatic mapping and localization in large-scale cycle using KNN

Most of the functions imbedded on robotic systems are highly dependent on positioning algorithm. system need to be designed in such way that accurate positioning can be ensured while object movements. Indoor positioning system is imposing great challenge since it cannot be linked to GPS system. Hence, location optimization and positioning process at indoor systems need to be performed using own (internal) positioning algorithms that depends on local sensors integrated with the mobile object itself. The results shown that total consumption time (which was used as performance metric to judge the used algorithms) is maximum with Spearman method which was equal to 0.00661 seconds whereas it is far less when Correlation method is used (equal to 000234 second).