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Sensor-network-based navigation of delivery robot for baggage handling in international airport
International Journal of Advanced Robotic Systems ( IF 2.1 ) Pub Date : 2020-07-01 , DOI: 10.1177/1729881420944734
Kefei Shen 1 , Chen Li 2 , Difei Xu 2 , Weihong Wu 2 , He Wan 2
Affiliation  

Automated guided vehicles (AGVs) have been regarded as a promising means for the future delivery industry by many logistic companies. Several AGV-based delivery systems have been proposed, but they generally have drawbacks in delivering and locating baggage by magnet line, such as the high maintenance cost, and it is hard to change the trajectory of AGV. This article considers using multi-AGVs as delivery robots to coordinate and sort baggage in the large international airport. This system has the merit of enlarging the accuracy of baggage sorting and delivering. Due to the inaccurate transportation efficiency, a time-dependent stochastic baggage delivery system is proposed and a stochastic model is constructed to characterize the running priority and optimal path planning for multi-AGVs according to the flight information. In the proposed system, ultra-wideband technology is applied to realize precisely positioning and navigation for multi-AGVs in the baggage distribution center. Furthermore, the optimal path planning algorithm based on time-window rules and rapidly exploring random tree algorithm is considered to avoid collision and maneuverability constraints and to determine whether the running path for each AGV is feasible and optimal. Computer simulations are conducted to demonstrate the performance of the proposed method.

中文翻译:

基于传感器网络的国际机场行李搬运机器人导航

自动导引车 (AGV) 已被许多物流公司视为未来交付行业的一种有前途的手段。已经提出了几种基于AGV的传送系统,但它们在通过磁力线传送和定位行李方面普遍存在维护成本高、AGV轨迹难以改变等缺点。本文考虑使用多AGV作为运送机器人在大型国际机场协调和分拣行李。该系统具有提高行李分拣和递送准确性的优点。针对运输效率不准确的问题,提出了一种基于时间的随机行李配送系统,并构建了随机模型来表征多AGV根据航班信息的运行优先级和最优路径规划。在提议的系统中,应用超宽带技术,实现行李配送中心多台AGV的精准定位导航。此外,考虑了基于时间窗规则和快速探索随机树算法的最优路径规划算法,以避免碰撞和机动性约束,并确定每个AGV的运行路径是否可行和最优。进行计算机模拟以证明所提出方法的性能。考虑基于时间窗规则和快速探索随机树算法的最优路径规划算法,以避免碰撞和机动性约束,并确定每个AGV的运行路径是否可行和最优。进行计算机模拟以证明所提出方法的性能。考虑基于时间窗规则和快速探索随机树算法的最优路径规划算法,以避免碰撞和机动性约束,并确定每个AGV的运行路径是否可行和最优。进行计算机模拟以证明所提出方法的性能。
更新日期:2020-07-01
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