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- W4308743808 abstract "To solve the problem of path optimisation and obstacle avoidance of automated guided vehicles (AGV) in the horizontal transportation of container terminals, this study proposed three operation modes of terminal vehicles and summarised four vehicle behaviour modes. Considering the vehicle behaviour pattern as the top-level object, based on heuristic rules and an object-oriented timed coloured stochastic Petri network (OOTCSPN) algorithm, a scheduling framework model of the AGV was established to optimise vehicle scheduling. A path planning model for three vehicle operation modes was designed for AGV path planning and real-time random obstacle avoidance based on the A-star(A*) algorithm fusion dynamic window approach (DWA). The simulation results indicate that the container handling efficiency increased by 13.2% using the improved algorithm. The scaled-down experiment confirms that the proposed method makes the planned path smoother and can also achieve real-time obstacle avoidance." @default.
- W4308743808 created "2022-11-15" @default.
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- W4308743808 date "2022-12-01" @default.
- W4308743808 modified "2023-09-30" @default.
- W4308743808 title "Control optimisation of automated guided vehicles in container terminal based on Petri network and dynamic path planning" @default.
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- W4308743808 doi "https://doi.org/10.1016/j.compeleceng.2022.108471" @default.
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