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Mansor, Mohd Asri; Morris, Alan S.

doi:10.1023/a:1008047425796

Cited by 16 publications

(3 citation statements)

References 10 publications

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“…In the warehousing workshop of the logistics storage system, the operating environment of AGVs is relatively complex. In order to analyze and study the problems more effectively, this paper adopts the grid method 15 to establish an environmental map model 16 and preprocesses the dataset provided in the question.…”

Section: Data Preprocessing and Model Preparationmentioning

confidence: 99%

“…Consequently, AGVs may obstruct each other in these narrow passages during the process of picking up goods. Assuming all AGVs operate at the same constant speed, the types of conflicts among AGVs in the warehouse can be classified as follows, based on the actual situation within the warehouse: Task7 (9,20), (9,19), (9,18), (9,17), (9,16), (9,15), (9,14), (9,13), (10,13), (11,13), (12,13), (13,13), (13,13), (12,13), (11,13), (10,13), (9,13), (9,14), (9,15), (9,16), (9,17), (9,18), (9,19), (9,20), (9,21), (9,…”

Section: Collision and Deadlock Analysismentioning

confidence: 99%

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Multi objective optimization scheduling of unmanned warehouse handling robots based on A star algorithm

Li,

Wang

2024

Concurrency and Computation

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SummaryThe sorting efficiency of the warehouse management and handling robots (automated guided vehicles [AGVs]) in an unmanned warehouse affects the delivery and lead time of orders. Studying the collaborative sorting of multiple AGVs can significantly improve work efficiency. The goal of this paper is to minimize the overall shortest transportation path and time while ensuring the completion of all orders and corresponding recycling or return tasks. This paper conducts experiments on global path planning for multiple AGVs based on the A* algorithm, both without considering collision and deadlock situations, and considering collision and deadlock situations. The results show that without considering collision and deadlock situations, the method of matching fixed storage locations and picking stations can improve overall efficiency, while considering collision and deadlock problems will result in reduced efficiency. In the future, the model will be further optimized taking into account actual conditions to improve overall efficiency.

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Section: Data Preprocessing and Model Preparationmentioning

confidence: 99%

Section: Collision and Deadlock Analysismentioning

confidence: 99%

Multi objective optimization scheduling of unmanned warehouse handling robots based on A star algorithm

Li,

Wang

2024

Concurrency and Computation

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“…Grid algorithm (Mansor and Morris, 1999 ) is to use encoded raster to represent the map; the raster containing obstacles is labeled as an obstacle raster, and vice versa is a free raster, which is used as the basis for path search. The Grid algorithm is generally used as an environmental modeling technique for path planning, and it is difficult to solve the problem of complex environmental information as a path planning method.…”

Section: Related Workmentioning

confidence: 99%

Optimization of robotic path planning and navigation point configuration based on convolutional neural networks

Wu,

Li,

et al. 2024

Front. Neurorobot.

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This study introduces a novel approach for enhancing robotic path planning and navigation by optimizing point configuration through convolutional neural networks (CNNs). Faced with the challenge of precise area coverage and the inefficiency of traditional traversal and intelligent algorithms (e.g., genetic algorithms, particle swarm optimization) in point layout, we proposed a CNN-based optimization model. This model not only tackles the issues of speed and accuracy in point configuration with Gaussian distribution characteristics but also significantly improves the robot's capability to efficiently navigate and cover designated areas with high precision. Our methodology begins with defining a coverage index, followed by an optimization model that integrates polygon image features with the variability of Gaussian distribution. The proposed CNN model is trained with datasets generated from systematic point configurations, which then predicts optimal layouts for enhanced navigation. Our method achieves an experimental result error of <8% on the test dataset. The results validate effectiveness of the proposed model in achieving efficient and accurate path planning for robotic systems.

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Path space approach for planning 2d shortest path based on elliptic workspace geometry mapping

Namgung¹

2004

KSME International Journal

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A new algorithm for planning a collision-free path based on algebraic curve is developed and the concept of collision-free Path Space (PS) is introduced. This paper presents a Geometry Mapping (GM) based on two straight curves in which the intermediate connection point is organized in elliptic locus (t3, 0). The GM produces two-dimensional PS that is used to create the shortest collision-free path. The elliptic locus of intermediate connection point has a special property in that the total distance between the focus points through a point on ellipse is the same regardless of the location of the intermediate connection point on the ellipse. Since the radial distance, 8, represents the total length of the path, the collision-free path can be found as the GM proceeds from 8----0 (the direct path) to ~=~max(the longest path) resulting in the minimum time search. The GM of elliptic workspace (EWS) requires calculation of interference in circumferential direction only. The procedure for GM includes categorization of obstacles to reduce necessary calculation. A GM based on rectangular workspace (RWS) using Cartesian coordinate is also considered to show yet another possible GM. The transformations of PS among Circular Workspace Geometry Mapping (CWS GM), Elliptic Workspace Geometry Mapping (EWS GM), and Rectangular Workspace Geometry Mapping (RWS GM), are also considered. The simulations for the EWS GM on various computer systems are carried out to measure performance of algorithm and the results are presented.

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Cited by 16 publications

References 10 publications

Multi objective optimization scheduling of unmanned warehouse handling robots based on A star algorithm

Multi objective optimization scheduling of unmanned warehouse handling robots based on A star algorithm

Optimization of robotic path planning and navigation point configuration based on convolutional neural networks

Path space approach for planning 2d shortest path based on elliptic workspace geometry mapping

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