| 1. |
- Al-Najjar, Basim, 1954-, et al.
(författare)
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SmartPro Vinnova Report
- 2021
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Rapport (refereegranskat)abstract
- This report presents the findings of WP2 with respect to challenges and use-cases relevant to smart production and maintenance systems. WP2 gathers information and determines the challenges the industrial partners (Astra Zeneca and Ericsson) in Sweden and India have. These challenges have been translated into concrete problems and purposes, which finally describes a main project problem and purpose. WP2 also focuses on specific use cases where smart automation and information gathering can help relieve potential bottlenecks. An exhaustive study of technologies and challenges has also been included. It is the view of WP2 that smart production maintenance technologies should be bundled with other solutions to have an increased impact within factory production systems. At the current stage, production maintenance is a secondary aspect in both Astra Zeneca and Ericsson factories.
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| 2. |
- Jörgensen, Nils, et al.
(författare)
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RoboPlan5G : Coordinating Cloud-Controlled Mobile Robots with 5G Network Configuration
- 2023
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Ingår i: 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation, ETFA 2023. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- With the emergence of Industry 4.0, comes an increasing need for multi-robot coordination and communication to efficiently complete joint tasks. A critical technology is the fifth generation (5G) mobile network, which enables cloud-controlled robots to execute tasks with differentiated quality-of-service (QoS) features. While there has been significant research on multi-robot planning, the integration with the capabilities of realistic network systems has been limited. In this paper, we introduce RoboPlan5G, a framework for 5G-aware robot planning. We propose a joint state-search model that includes task planning coordination in conjunction with 5G physical resource block (PRB) allocation. This process ensures efficient usage of the limited indoor 5G spectrum and effective service performance, while still aiming for the completion of tasks in the shortest possible time frame. Scenarios are generated in an Industry 4.0 environment, where the planner is shown to decrease the required 5G spectrum allocation by 50%, and on average improve the plan quality by 45% while maintaining a small computation time.
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| 3. |
- Jörgensen, Nils, et al.
(författare)
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Towards 5G-Aware Robot Planning for Industrial Applications
- 2022
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Ingår i: 2022 IEEE 27th international conference on emerging technologies and factory automation (ETFA). - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- With the emergence of Industry 4.0, comes an increasing need for multi-robot coordination and communication to efficiently complete joint tasks. A critical technology is the fifth generation (5G) mobile network, which enables multiple robots to execute control tasks with differentiated quality-of-service (QoS) features. However, there has been limited analysis of the impact of real 5G capabilities on multi-agent robot planning problems. In this paper, we provide a review of robot planning algorithms suitable for industrial use-cases, which consider communication aspects in the planning formulation. The paper is further positioned to identify gaps in existing state of the art within communication-aware planning. This is followed by an analysis of key challenges to be targeted at the intersection of 5G, Industry 4.0 and multi-agent robot planning. This analysis is strategically important and would prove useful to academic researchers and industry experts focusing on deployment of robots in industrial settings.
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