Global localization of automated guided vehicles in wireless networks

Lategahn, Julian; Müller, Marcel; Röhrig, Christof

doi:10.1109/idaacs-sws.2012.6377621

Cited by 8 publications

(3 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Even though we have complete knowledge of the robot's interior, analyzing and designing self-organizing systems like swarm robotics remains a difficult task (Aloui et al 2020). For this, (Lategahn et al 2012) proposed an integrated methodology based on the principles of swarm robotics to design a swarm of automated guided vehicles (AGVs).…”

Section: Related Workmentioning

confidence: 99%

Development of an AGV System Using MBSE Method and Multi-agents’ Technology

Aloui

Hammadi

Guizani

et al. 2022

Lecture Notes in Mechanical Engineering

View full text Add to dashboard Cite

Today, smart manufacturing is differentiated from many other initiatives by its emphasis on human ingenuity. Human capabilities must be enhanced by intelligently designing a customized solution for a specific domain. For example, Industry 4.0 is based on collaborative robots that digitize and simplify manufacturing processes. In fact, Automatic Guided Vehicles (AGVs) are widely used in intelligent industries due to their productivity, flexibility, and versatility. They are widely considered as one of the most important tools for flexible logistics in workshops. They can move materials and products without a predefined route. Many commercially available AGVs provide a self-guided navigation system to find their way to target workstations. However, many developers and producers of industrial robots face several challenges in designing AGV systems, such as the difficulty of defining a decentralized system decision as well as the discontinuity and complexity of the design process. In this article, we propose a new design approach based on multi-agent technology and the Model-based systems engineering method (MBSE) to meet the challenges of functional, physical, and software integration. It is a top-down approach from requirements specification, functional and structural modeling using the systems modeling language (SysML) to model simulation with the multi-agent tool (Anylogic). Our design approach was applied on an Automated Guided Vehicle (AGV) system to serve items and deliver parts and supplies to stations in a smart factory.

show abstract

Section: Related Workmentioning

confidence: 99%

Development of an AGV System Using MBSE Method and Multi-agents’ Technology

Aloui

Hammadi

Guizani

et al. 2022

Lecture Notes in Mechanical Engineering

View full text Add to dashboard Cite

show abstract

“…Analyzing and designing self-organizing systems like swarm robotics is a challenging task even though we have complete knowledge about the robot's interior [22]. In addition, Lategahn et al [23] proposed an integrated methodology based on swarm robotics principles to designing a swarm of small automated guided vehicles (AGVs). This swarm of robots was used to collect items from store shelves and take them to a picking station.…”

Section: Related Workmentioning

confidence: 99%

Integrated Design Methodology of Automated Guided Vehicles Based on Swarm Robotics

et al. 2021

View full text Add to dashboard Cite

In recent years, collaborative robots have become one of the main drivers of Industry 4.0. Compared to industrial robots, automated guided vehicles (AGVs) are more productive, flexible, versatile, and safer. They are used in the smart factory to transport goods. Today, many producers and developers of industrial robots have entered the AGV sector. However, they face several challenges in designing AGV systems, such as the complexity and discontinuity of the design process, as well as the difficulty of defining a decentralized system decision. In this paper, we propose a new integrated design methodology based on swarm robotics to address the challenges of functional, physical, and software integration. This methodology includes two phases: a top-down phase from requirements specification to functional and structural modeling using the systems modeling language (SysML); with a bottom-up phase for model integration and implementation in the robot operating system (ROS). A case study of an automated guided vehicle (AGV) system was chosen to validate our design methodology and illustrate its contributions to the efficient design of AGVs. The novelty of this proposed methodology is the combination of SysML and ROS to address traceability management between the different design levels of AGV systems, in order to achieve functional, physical and software integration.

show abstract

“…The estimator is useful for mitigating effect of channel disturbance that may jeopardize the robustness of the close loop wireless-based AGV networked control system Authors emphasized that although AGV controls are traditionally implemented locally on the AGV, however benefits of implementing wireless communication based networked control system for AGV include better fleet management and improved task coordination that can lead to the actualization of a reliable FMS [248]. In [249], authors proposed the use of IEEE 802.15.4a CSS (chirp spread spectrum) to improve on swarm AGV global localization in an industrial environment. To improve on localization and tracking of a swarm of AGVs in the industrial environment, authors' uses the IEEE 802.15.4a CSS to fuse wheel encoder data from a sensor in conjunction with AGV range measurement.…”

Section: Also Discussed the Design Of A Cheap Wi-fi Based Agv Called Cheap Cooperative Agv (Ccagv) Ccagv Uses The Esp8266mentioning

confidence: 99%

A Review of Recent Advances in Automated Guided Vehicle Technologies: Integration Challenges and Research Areas for 5G-Based Smart Manufacturing Applications

et al. 2020

View full text Add to dashboard Cite

In industrial environments, over several decades, Automated Guided Vehicles (AGVs) and Autonomous Mobile Robots (AMRs) have served to improve efficiencies of intralogistics and material handling tasks. However, for system integrators, the choice and effective deployment of improved, suitable and reliable communication and control technologies for these unmanned vehicles remains a very challenging task. Specifics of communication for AGVs and AMRs imposes stringent performance requirements on latency and reliability of communication links which many existing wireless technologies struggle to satisfy. In this paper, a review of latest AGVs and AMRs research results in the past decade is presented. The review encompasses results from different past and present research domains of AGVs. In addition, performance requirements of communication networks in terms of their latencies and reliabilities when they are deployed for AGVs and AMRs coordination, control and fleet management in smart manufacturing environments are discussed. Integration challenges and limitations of present state-of-the-art AGV and AMR technologies when those technologies are used for facilitating AGV-based smart manufacturing and factory of the future applications are also thoroughly discussed. The paper also present a thorough discussion of areas in need of further research regarding the application of 5G networks for AGVs and AMRs fleet management in smart manufacturing environments. In addition, novel integration ideas by which tactile Internet, 5G network slicing and virtual reality applications can be used to facilitate AGV and AMR based factory of the future (FoF) and smart manufacturing applications were motivated.INDEX TERMS Intelligent factory, factory of the future, 5G, smart manufacturing, industry 4.0, autonomous industrial equipment, AGV, AMR, tactile Internet, virtual reality, lean manufacturing.

show abstract

Global localization of automated guided vehicles in wireless networks

Cited by 8 publications

References 10 publications

Development of an AGV System Using MBSE Method and Multi-agents’ Technology

Development of an AGV System Using MBSE Method and Multi-agents’ Technology

Integrated Design Methodology of Automated Guided Vehicles Based on Swarm Robotics

A Review of Recent Advances in Automated Guided Vehicle Technologies: Integration Challenges and Research Areas for 5G-Based Smart Manufacturing Applications

Contact Info

Product

Resources

About