Path Planning and Control for Multiple AGVs Based on Improved Two-Stage Traffic Scheduling
Lou Peihuang, Wu Xing, and Wang Jiarong
Nanjing University of Aeronautics and Astronautics
29 YuDao Street, Nanjing, PR China
An improved two-stage traffic scheduling algorithm for path planning and conflict avoidance of multiple AGVs (Automated Guided Vehicle) is combined with an adaptive motion control algorithm for path following of a single AGV in this paper, in order to implement an integrated planning and control system. A genetic algorithm (GA) is used for feasible path planning both offline and online. Multiple objectives and constraints are added to the online GA when some digital map routes cannot be used due to unavoidable conflict. The conflict-free policy we propose changes the speed or route of the AGV with a lower priority to make the conflict settled. Adaptive motion control enables individual AGV to follow the planned paths at any given speed. The planned paths and given speed are the information links connecting traffic scheduling and motion control. Numerical simulation confirms the effectiveness of our traffic scheduling algorithm and the adaptability of the motion control algorithm.
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