Citrus greening (Huanglongbing) has caused significant financial loss in many states of the United States and worldwide. In recent years, a heat therapy method has been investigated to prolong the production period of the diseased citrus trees after infection. One crucial step in this heat treatment process is to precisely align the truck with the diseased tree to reduce the operation time during deployment of the treatment tent. In this study, a binocular vision system is used to detect the position of the diseased tree relative to the truck, and a direct based path planning method is used to generate a nominal, optimal path for the truck to follow. A driver's eye perception model is derived, simulating the distortion due to the human eye's perception of objects on the computer screen, which will be used in the truck controller. A linear quadratic controller is then designed to compensate for the error coming from the eye perception mismatches and sensor and actuator noise. The studied human augmented driving control system can significantly reduce the operation time as the driver doesn't have to constantly get out of the cab to check the truck-tree alignment. Simulation results show the effectiveness of the proposed system.
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