Trajectory Prediction of Moving Workers for Autonomous Mobile Robots on the Shop Floor

Löcklin, Andreas; Artelt, Maurice; Ruppert, Tamás; Vietz, Hannes; Jazdi, Nasser; Weyrich, Michael

doi:10.1109/etfa52439.2022.9921493

Cited by 2 publications

(3 citation statements)

References 28 publications

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“…In [61], the work of the AGV was based on human behavior and was analogous to nature, so the AGV work was more predictable and understandable for workers. A similar approach was presented in the research prepared by [108], where AGVs could anticipate human behaviors and predict their trajectory because human movements are usually directly motivated by their tasks. In [62], a controller was proposed, which mimics the standards of human vehicle control, for example, "situation-aware speed adjustment on curved paths".…”

Section: Human-agv Cooperationmentioning

confidence: 99%

“…Therefore, articles in this group focused on technologies and methods for collecting real-time data on elements on the AGV route. In the analyzed publications, this data was directly collected by the transport device [95][96][97][98], by using cameras [96,[98][99][100][101][102], laser sensors [95,[99][100][101][103][104][105], and ultrasound [95], as well as indirectly, using sensors located on a human (Ultra-wideband system-UWB) [99,104,[106][107][108]. In some articles, hybrid solutions were presented [101,103,104,109,110,112].…”

Section: Designing a Safe Work Environmentmentioning

confidence: 99%

“…The critical aspect is the navigation system, which allows the AGV to smoothly move along the designated route. For this purpose, appropriate programs, algorithms, and systems are created, responsible for the correct movement of AGVs along fixed routes [108,[113][114][115][116][117][118][119][120][121][122][123][124]. Regarding navigation, it is also crucial that the AGV continues the task in the event of a disturbance (e.g., an obstacle).…”

Section: Designing a Safe Work Environmentmentioning

confidence: 99%

See 2 more Smart Citations

Interaction between a Human and an AGV System in a Shared Workspace—A Literature Review Identifying Research Areas

Tubis,

Poturaj,

Smok

2024

Sustainability

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Background: This article presents the results of a literature review from 2018 to 2023, which focused on research related to human and AGV system cooperation in a shared workspace. This study defines AGV systems as systems using Automated Guided Vehicles or Autonomous Guided Vehicles. An Automated Guided Vehicle is a cart that follows a guided path, while an Autonomous Guided Vehicle is an Automated Guided Vehicle that is autonomously controlled. The analyses conducted answered two research questions: (RQ1) In what aspects are the human factor examined in publications on the implementation and operation of AGV systems? (RQ2) Has the human-AGV collaboration aspect been analyzed in the context of a sustainable work environment? Methods: The literature review was conducted following the systematic literature review method, using the PRISMA approach. Results: Based on the search of two journal databases, according to the indicated keywords, 1219 documents pertaining to the analyzed issues were identified. The selection and elimination of documents that did not meet the defined criteria made it possible to limit the number of publications to 117 articles and proceedings papers. On this basis, the authors defined a classification framework comprising five basic research categories and nine subcategories. The analyzed documents were classified, and each distinguished group was characterized by describing the results. Conclusions: The development of a two-level classification framework for research from the analyzed area according to the assumptions of the concept map and the identification of research gaps in the area of human-AGV interaction.

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Section: Human-agv Cooperationmentioning

confidence: 99%

Section: Designing a Safe Work Environmentmentioning

confidence: 99%

Section: Designing a Safe Work Environmentmentioning

confidence: 99%

See 1 more Smart Citation

Interaction between a Human and an AGV System in a Shared Workspace—A Literature Review Identifying Research Areas

Tubis,

Poturaj,

Smok

2024

Sustainability

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Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review

Belter,

Hering,

Weichbroth

2023

Applied Sciences

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Background: In the context of Warehouse Management Systems, knowledge related to motion trajectory prediction methods utilizing machine learning techniques seems to be scattered and fragmented. Objective: This study seeks to fill this research gap by using a systematic literature review approach. Methods: Based on the data collected from Google Scholar, a systematic literature review was performed, covering the period from 2016 to 2023. The review was driven by a protocol that comprehends inclusion and exclusion criteria to identify relevant papers. Results: Considering the Warehouse Management Systems, five categories of motion trajectory prediction methods have been identified: Deep Learning methods, probabilistic methods, methods for solving the Travelling-Salesman problem (TSP), algorithmic methods, and others. Specifically, the performed analysis also provides the research community with an overview of the state-of-the-art methods, which can further stimulate researchers and practitioners to enhance existing and develop new ones in this field.

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Trajectory Prediction of Moving Workers for Autonomous Mobile Robots on the Shop Floor

Cited by 2 publications

References 28 publications

Interaction between a Human and an AGV System in a Shared Workspace—A Literature Review Identifying Research Areas

Interaction between a Human and an AGV System in a Shared Workspace—A Literature Review Identifying Research Areas

Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review

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