Automated guided vehicles position control: a systematic literature review

Reis, Wallace Pereira Neves dos; Couto, Giselle Elias; Morandin, Orides

doi:10.1007/s10845-021-01893-x

Cited by 39 publications

(17 citation statements)

References 123 publications

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“…The primary objective of conducting a SLR is to comprehensively identify various optimization methods applied in both primary and secondary processes of PM to enhance the mechanical properties of PM materials. The systematic review has been conducted in accordance with the PRISMA flow diagram and reporting checklist [19,20]. The PRISMA 2020 flow diagram was followed in the study selection process as shown in figure 1, which contains three phases of study selection process, identification, screening and inclusion of relevant articles.…”

Section: Systematic Literature Review (Slr)mentioning

confidence: 99%

Optimization methods in powder metallurgy for enhancing the mechanical properties: a systematic literature review

Lingam,

Ananthanarayanan,

Jeevanantham

et al. 2024

Eng. Res. Express

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Powder metallurgy offers several advantages over traditional manufacturing methods, such as improved material utilization and waste reduction. The powder metallurgy process involves four primary steps, metal powder preparation, mixing, compaction, and sintering, followed by secondary operations such as forging, rolling, and extrusion. However, existing studies have predominantly focused on refining the primary processes, neglecting secondary processes that could further enhance mechanical properties. A systematic literature review following the Preferred Reporting Items for Systematic Review and Meta-Analysis method identified twenty-three relevant articles over a ten-year period, highlighting three main optimization methods, that are, the Taguchi method, Taguchi-based Grey Relational Analysis, and Response Surface Methodology. These methods effectively reduce experimental trials and optimize key parameters like compaction pressure and weight percentage, which significantly influence mechanical properties. The review emphasizes the key powder metallurgy process parameters that have a significant impact on mechanical properties, becoming the primary targets for optimization. It offers a focused examination of which process parameters require thorough investigation for optimization and the suitable optimization method to achieve optimal outcomes, whether for single or multiple responses, thereby enhancing the manufacturing process. However, inconsistencies in parameter significance across studies indicate the material-dependent nature of powder metallurgy materials. The review also identifies a gap in the literature regarding secondary process optimization and comparative analyses of optimization methods. Future research should explore optimizing secondary processes in powder metallurgy, conduct comparative studies of different optimization methods, and develop novel approaches for optimization to further enhance mechanical properties and process efficiency.

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Section: Systematic Literature Review (Slr)mentioning

confidence: 99%

Optimization methods in powder metallurgy for enhancing the mechanical properties: a systematic literature review

Lingam,

Ananthanarayanan,

Jeevanantham

et al. 2024

Eng. Res. Express

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“…Finally, a recent interesting literature review on AGV control has been published by Reis et al As it states, both classical control and artificial intelligence-based techniques were primarily used in kinematic controllers [31]. The four topics addressed in this paper are: the control strategies used in the AGV position control problem, how the literature presents the AGV operating requirement of position accuracy, how the literature validates the proposed controller and presents their results regarding the system's position accuracy, and the technological tendencies the proposed solutions reveal.…”

Section: Related Workmentioning

confidence: 99%

“…It is noteworthy to remember that the action of the weight is not represented as it has been considered in the static case. Applying balance of forces and moments with respect to the geometric center of the AGV, the following equations are obtained (28)- (31).…”

Section: Ctmentioning

confidence: 99%

Performance and Extreme Conditions Analysis Based on Iterative Modelling Algorithm for Multi-Trailer AGVs

2022

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Automatic guidance vehicles (AGV) are industrial vehicles that play an important role in the development of smart manufacturing systems and Industry 4.0. To provide these autonomous systems with the flexibility that is required today in these industrial workspaces, AGV computational models are necessary in order to analyze their performance and design efficient planning and control strategies. To address these issues, in this work, the mathematical model and the algorithm that implement a computational control-oriented simulation model of a hybrid tricycle-differential AGV with multi-trailers have been developed. Physical factors, such as wheel-ground interaction and the effect of vertical and lateral loads on its dynamics, have been incorporated into the model. The model has been tested in simulation with two different controllers and three trajectories: a circumference, a square, and an s-shaped curve. Furthermore, it has been used to analyze extreme situations of slipping and capsizing and the influence of the number of trailers on the tracking error and the control effort. This way, the minimum lateral friction coefficient to avoid slipping and the minimum ratio between the lateral and height displacement of the center of gravity to avoid capsizing have been obtained. In addition, the effect of a change in the friction coefficient has also been simulated.

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“…LiDAR is one of the most widely used long‐range perception technologies in vehicles as automation levels increase. Its use has been extended to other sectors, such as the industrial sector in manufacturing plants [33] or in large machinery. However, operation in road vehicles has influenced the progress of hardware and software.…”

Section: Introductionmentioning

confidence: 99%

LiDAR point clouds analysis computer tools for teaching autonomous vehicles perception algorithms

Jiménez,

Clavijo

2024

Comp Applic In Engineering

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The technological developments behind autonomous vehicles cover several areas and engineers training in this field represents a challenge. The main layers include perception, decision making, and acting. In the first one, different technologies can be used. The processing of the information provided by the sensors must allow successive modules to understand the environment and Laser imaging Detection and Ranging (LiDAR) technology is one of the most promising ones nowadays for this task. It offers great robustness in detection, but the extraction of information from the point cloud involves the development of complex algorithms that could be very time‐consuming if an experimental teaching is intended. This article presents two educational solutions for deepening in perception algorithms using LiDAR for autonomous driving: a closed ad‐hoc computer application for two‐dimensional (2D) LiDAR point cloud processing and an oriented set of commands for three‐dimensional (3D) LiDARs in Matlab. Their use allows main concept exploration in practical sessions with little time consumption and provides students a general overview of the tasks that must be performed by the perception layer in the autonomous vehicles. Furthermore, these tools provide the possibility of organizing different activities in the classroom related to theoretical and experimental issues, and understanding of results because the most tedious tasks are eased.

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Automated guided vehicles position control: a systematic literature review

Cited by 39 publications

References 123 publications

Optimization methods in powder metallurgy for enhancing the mechanical properties: a systematic literature review

Optimization methods in powder metallurgy for enhancing the mechanical properties: a systematic literature review

Performance and Extreme Conditions Analysis Based on Iterative Modelling Algorithm for Multi-Trailer AGVs

LiDAR point clouds analysis computer tools for teaching autonomous vehicles perception algorithms

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