무인 지게차에서 센서 융합을 위한 위치 좌표 시스템
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Unmanned forklift has a great potential to enhance the productivity of material handling in dangerous applications because this forklift can pick up and deliver loads without an operator and any fixed guide. There are, however, many technical difficulties in developing unmanned forklift including localization, map building, sensor fusion, and control. Recently, NAV 200 positioning system is used localization system which is the most important factors of unmanned forklift, that is a laser measurement system for indoor localization with high accuracy and high precision. But it has some problem that it may not operate well when it moves fast or changes its direction an instant. In order to solve these problems, this paper proposes sensor fusion with dead reckoning using kinematics of the unmanned forklift and Kalman filter based prediction using tendency of movement.
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