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Fuzzy inference for crash avoidance of industrial lift trucks
(Selçuk Üniversitesi, 2022) Göçer, Gökçe; Taş, Muhammed Oğuz; Yavuz, Hasan Serhan
Industrial lift trucks, also shortly known as the forklifts, have limited viewing angles and accelerate rapidly. This situation may cause accidents in the work area and therefore the loss of property and time. In this study, the crash risk of the autonomous forklifts that cause accidents during backward movements in factories or warehouses is calculated by designing a fuzzy inference mechanism. This mechanism takes into account the backward speed of the vehicle and the distance between the object and the vehicle. A Simulink model has also been created for the designed system to take appropriate actions in collision avoidance. The proposed system was tested in a simulation environment assumed to be the factory environment having obstacles. As a result, we observed that the vehicle reached its destination by taking appropriate actions with successfully avoiding obstacles.