On the design for AGVs: Modeling, path planning and localization
Intelligent warehouse becomes a key component of logistics process automation, which essentially promotes the productivity and cost reduction. This paper presents a novel design solution of an Automated Guided Vehicles (AGVs) system for intelligent warehouse. An improved version of classical Dijkstra shortest path algorithm is proposed for efficient global path planning. In the case of multi AGV, the time windows method is used to address the issue of conflict and deadlock. In addition, the local path planning and auto localization is addressed by using a heuristics based algorithm and Monte Carlo Localization algorithm respectively. Extensive numerical experiments based on Player/Stage simulator are carried out to assess the suggested algorithms, for a range of scenarios and the result well validates its effectiveness. Currently the proposed design solution is adopted in developing the prototype of AGVs to be deployed in practice.
2011 IEEE International Conference on Mechatronics and Automation