Research on Optimization of Multi-AGV Path Based on Genetic Algorithm Considering Charge Utilization

Wang, Jianjun; Pan, Junnan; Huo, Jikun; Wang, Ran; Li, Li; Nian, Tiantian

doi:10.1088/1742-6596/1769/1/012052

Cited by 4 publications

(6 citation statements)

References 8 publications

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“…(6) The influence of shelves height on power consumption is considered. (7) The influence of acceleration and deceleration on power loss is not considered. (8) The energy loss caused by parking and waiting is not considered.…”

Section: Figure 1 the Forklift Agv And Three-dimensional Shelfmentioning

confidence: 99%

“…(6) The start time, end time, path, power consumption and other scheme information of the first task are saved. (7) The second task can be calculated through the above steps and the departure time can be determined (the departure time should be later than the current time of the vehicle).…”

Section: The Optimization Algorithm Of Agv Schedulingmentioning

confidence: 99%

“…The proposed method solves the problems of the number of AGVs, the assignment of AGVs to trucks, and the sequencing of assigned tasks [6]. Wang et al (2021) constructed a multi-AGV path optimization model in an unmanned storage environment based on the charging utilization rate. The model takes the shortest path and the highest charging utilization rate as the dual goals.…”

Section: Introductionmentioning

confidence: 99%

“…The model takes the shortest path and the highest charging utilization rate as the dual goals. However, static scheduling often ignores some dynamic factors in the transportation process [7].…”

Section: Introductionmentioning

confidence: 99%

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Scheduling Approach of Automatic Guided Vehicle Considering Equipment Failure and Power Management

Fan

Jiang²

2023

Preprint

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Predictive management on power consumption during static scheduling of outfitting automatic transportation equipment is very difficult. In addition, dynamic scheduling has poor response ability to sudden failures. To solve this problem, this paper proposes an AGV (Automatic Guided Vehicle) scheduling approach for outfitting warehouse considering equipment failure and power management. Firstly, based on the power consumption rate function, the power consumption model of AGV for transport task is established. According to the departure power and task consumption power, the charging time and the return time of the AGV are calculated. Secondly, the optimization model of AGV scheduling is established with the goal of minimizing the total transport time. Further, the variable definitions of overhaul and minor repair for AGV are made, and the scheduling strategy for sudden failure is proposed. Finally, an optimization algorithm based on power consumption and failure maintenance for outfitting vehicle scheduling is developed to solve the optimization model in a case. The proposed method can pre plan the charging time according to the vehicle power consumption. Rescheduling is carried out for sudden failure and charging return to improve the dynamic response capability of outfitting transport vehicles.

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Section: Figure 1 the Forklift Agv And Three-dimensional Shelfmentioning

confidence: 99%

Section: The Optimization Algorithm Of Agv Schedulingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Scheduling Approach of Automatic Guided Vehicle Considering Equipment Failure and Power Management

Fan

Jiang²

2023

Preprint

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“…The Automatic Guided Vehicle (AGV) plays a crucial role in the intelligent transportation system. AGVs are the primary automated equipment that carry materials and process unmanned distribution and sorting in an unmanned storage environment [11]. Path planning has been the most crucial consideration of mobile robot navigation, which plans the path from the start to the target for mobile robots [3].…”

Section: Related Workmentioning

confidence: 99%

A Dual-Layer Weight-Leader-Vicsek Model for Multi-AGV Path Planning in Warehouse

Lin,

Liu,

Wang

2023

Biomimetics

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Multiple automatic guided vehicles are widely involved in industrial intelligence. Path planning is crucial for their successful application. However, achieving robust and efficient path planning of multiple automatic guided vehicles for real-time implementation is challenging. In this paper, we propose a two-layer strategy for multi-vehicle path planning. The approach aims to provide fast computation and operation efficiency for implementation. The start–destination matrix groups all the vehicles, generating a dynamic virtual leader for each group. In the first layer, the hybrid A* algorithm is employed for the path planning of the virtual leaders. The second layer is named leader–follower; the proposed Weight-Leader-Vicsek model is applied to navigate the vehicles following their virtual leaders. The proposed method can reduce computational load and achieve real-time navigation by quickly updating the grouped vehicles’ status. Collision and deadlock avoidance is also conducted in this model. Vehicles in different groups are treated as dynamic obstacles. We validated the method by conducted simulations through MATLAB to verify its path-planning functionality and experimented with a localization sensor.

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Indoor Navigation of an Autonomous Guided Vehicle Using ArUco Markers

Figueiredo,

Pereira,

Vasques

2023

Springer Proceedings in Earth and Environmental Sciences

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Research on Optimization of Multi-AGV Path Based on Genetic Algorithm Considering Charge Utilization

Cited by 4 publications

References 8 publications

Scheduling Approach of Automatic Guided Vehicle Considering Equipment Failure and Power Management

Scheduling Approach of Automatic Guided Vehicle Considering Equipment Failure and Power Management

A Dual-Layer Weight-Leader-Vicsek Model for Multi-AGV Path Planning in Warehouse

Indoor Navigation of an Autonomous Guided Vehicle Using ArUco Markers

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