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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ASME 2018 Dynamic Systems and Control Conference
September 30–October 3, 2018
Atlanta, Georgia, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-5191-3
PROCEEDINGS PAPER
Path Control of a Heat Treatment Truck Considering Driver-Vehicle Interaction
Andong Dai,
Andong Dai
University of Central Florida, Orlando, FL
Search for other works by this author on:
Yunjun Xu
Yunjun Xu
University of Central Florida, Orlando, FL
Search for other works by this author on:
Andong Dai
University of Central Florida, Orlando, FL
Yunjun Xu
University of Central Florida, Orlando, FL
Paper No:
DSCC2018-9040, V003T32A006; 8 pages
Published Online:
November 12, 2018
Citation
Dai, A, & Xu, Y. "Path Control of a Heat Treatment Truck Considering Driver-Vehicle Interaction." Proceedings of the ASME 2018 Dynamic Systems and Control Conference. Volume 3: Modeling and Validation; Multi-Agent and Networked Systems; Path Planning and Motion Control; Tracking Control Systems; Unmanned Aerial Vehicles (UAVs) and Application; Unmanned Ground and Aerial Vehicles; Vibration in Mechanical Systems; Vibrations and Control of Systems; Vibrations: Modeling, Analysis, and Control. Atlanta, Georgia, USA. September 30–October 3, 2018. V003T32A006. ASME. https://doi.org/10.1115/DSCC2018-9040
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