Research on online scheduling and charging strategy of robots based on shortest path algorithm
Research on online scheduling and charging strategy of robots based on shortest path algorithm
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基于最短路径算法的机器人在线调度与充电策略研究
DOI：
10.1016/j.cie.2021.107097
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发表时间：
2021-03
影响因子：
7.9
通讯作者：
Wang Jiaxin
中科院分区：
文献类型：
--
作者：
Fu Xiao;Cheng Zongmao;Wang Jiaxin
近年来，移动的充电器在移动的充电器（MC）的能量补充方面的应用越来越受到关注。研究了移动路径未知的仓库中机器人的在线调度和充电策略。首先，本文将存储场景抽象为网格模型。其次，提出了一种在机器人任务优先的前提下，基于坐标差的最短路径算法。然后，通过随机模拟确定了MC的最小服务量。最后，利用M scinM scinn scinm ∞ scinm FCFS模型计算机器人的平均充电延迟。通过仿真分析可以发现，MC的平均服务率与机器人的平均充电时延成反比。随着时间的增加，MC接收到的计费请求的数量也线性上升。然而，在Δ t的固定时间长度中，充电请求的数量近似为固定值。此外，MC接收到的充电请求的数量与机器人的总数之间存在线性正相关。当机器人总数不变时，仓库中MC越多，机器人的平均充电延迟越小，但有下界。本文提出的机器人在线调度和充电策略适用于大多数存储场景。为进一步研究机器人移动的充电调度策略提供了一种新的思路。
In recent years, the employment of mobile chargerson energy supplementation of mobile charger (MC) has received increasing attention. This paper focuses on the online scheduling and charging strategies of robots in warehouses with unknown moving paths. First, the storage scenario is abstracted to a grid model in this article. Secondly, a shortest path algorithm based on coordinate difference under the premise of giving priority to the robot task is proposed. Then, the minimum service quantity of MC is determined through random simulation. Last but not least, the model of M∕ M∕ n∕∞∕ m∕ FCFS is used to calculate the average charging delay of the robot. Through simulation analysis, it can be found that the average service rate of MC is inversely proportional to the average charging delay of the robot. As time increases, the number of charging requests received by the MC also rises linearly. However, in a fixed length of time of Δ t, the number of charging requests is approximately a fixed value. Moreover, there is a linear positive correlation between the number of charging requests received by the MC and the total number of robots. When the total number of robots stays unchanged, the more MCs in the warehouse, the smaller the average charging delay of the robot will be yet with lower bound. The robot online scheduling and charging strategy proposed in this paper is applicable for most storage scenarios. Further, it contributes a new idea for further research on robot mobile charging scheduling strategy.
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DOI：
10.1145/2633675.2633676
发表时间：
2014-08
期刊：
--
影响因子：
--
作者：
R. Beigel;Jie Wu;Huanyang Zheng
通讯作者：
R. Beigel;Jie Wu;Huanyang Zheng
影响因子：
6.3
作者：
Changlin Yang;Kwan-Wu Chin
通讯作者：
Changlin Yang;Kwan-Wu Chin
影响因子：
10.6
作者：
Na, Woongsoo;Park, Junho;Cho, Sungrae
通讯作者：
Cho, Sungrae
影响因子：
7.9
作者：
Haipeng Dai;K. Sun;A. Liu;Lijun Zhang;Jiaqi Zheng;Guihai Chen
通讯作者：
Haipeng Dai;K. Sun;A. Liu;Lijun Zhang;Jiaqi Zheng;Guihai Chen
DOI：
10.1109/iccse.2011.6028822
发表时间：
2011-09
期刊：
2011 6th International Conference on Computer Science & Education (ICCSE)
影响因子：
--
作者：
Josh D. Freeman;Simi S Amrita;Amrita Vishwa Vidyapeetham
通讯作者：
Josh D. Freeman;Simi S Amrita;Amrita Vishwa Vidyapeetham