| 1. |
- Gürdür, Didem, 1983-, et al.
(författare)
-
Knowledge Representation of Cyber-physical Systems for Monitoring Purpose
- 2018
-
Ingår i: 51st CIRP Conference on Manufacturing Systems. - : Elsevier. ; , s. 468-473
-
Konferensbidrag (refereegranskat)abstract
- Automated warehouses, as a form of cyber-physical systems (CPSs), require several components to work collaboratively to address the common business objectives of complex logistics systems. During the collaborative operations, a number of key performance indicators (KPI) can be monitored to understand the proficiency of the warehouse and control the operations and decisions. It is possible to drive and monitor these KPIs by looking at both the state of the warehouse components and the operations carried out by them. Therefore, it is necessary to represent this knowledge in an explicit and formally-specified data model and provide automated methods to derive the KPIs from the representation. In this paper, we implement a minimalistic data model for a subset of warehouse resources using linked data in order to monitor a few KPIs, namely sustainability, safety and performance. The applicability of the approach and the data model is illustrated through a use case. We demonstrate that it is possible to develop minimalistic data models through Open Services for Lifecycle Collaboration (OSLC) resource shapes which enables compatibility with the declarative and procedural knowledge of automated warehouse agents specified in Planning Domain Definition Language (PDDL).
|
|
| 2. |
- Jörgensen, Nils, et al.
(författare)
-
RoboPlan5G : Coordinating Cloud-Controlled Mobile Robots with 5G Network Configuration
- 2023
-
Ingår i: 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation, ETFA 2023. - : Institute of Electrical and Electronics Engineers (IEEE).
-
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.
|
|
| 3. |
- Jörgensen, Nils, et al.
(författare)
-
Towards 5G-Aware Robot Planning for Industrial Applications
- 2022
-
Ingår i: 2022 IEEE 27th international conference on emerging technologies and factory automation (ETFA). - : Institute of Electrical and Electronics Engineers (IEEE).
-
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.
|
|
