Mathematical Sciences

<h4>Graph Neural Network for Mobile Robot</h4>
<p>Place: MV:L14, Chalmers tvärgata 3</p>
<p>Abstract: Mobile Robotics play a crucial role in modern intralogistics for both factories and warehouses, where they save labour and reduce damages to goods. The dominating technology for Mobile Robots in intralogistics is Automated Guided Vehicles, which is the focus of this thesis. In AGV systems, the vehicle fleet moves within a fix network of virtual roads, defining the physical trajectories that the vehicles must adhere to.</p>
<p>A critical step of applying an AGV system is ensuring that the design of the road network results in the desired throughput and efficiency. Here, traffic prediction can provide important insights, complementing the traditional and time-consuming approach of simulationThe inherent graph-representable nature of AGV systems makes Graph Representation Learning a natural choice for traffic prediction. This thesis explores the application of Graph Neural Networks (GNNs), which is, to our knowledge, a novel approach for predicting AGV system behavior, laying the foundation for GNN research in this field. We conducted a theoretical investigation and proposed a novel hierarchical GNN framework tailored for AGV systems. Additionally, we performed experiments based on datasets generated from AGV system simulations to explore the design space of GNNs. The results demonstrate that the best-performing GNN model achieves promising performance, showing its potential for future deployment in AGV system design.</p>

<h4><span style="font-size: 12.0pt; font-family: 'Aptos',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Aptos; color: black; mso-ansi-language: SV; mso-fareast-language: SV; mso-bidi-language: AR-SA;">Minimising cycle time in an assembly&nbsp;line with human workers</span></h4>
<p><span style="font-size: 12.0pt; font-family: 'Aptos',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Aptos; color: black; mso-ansi-language: SV; mso-fareast-language: SV; mso-bidi-language: AR-SA;">Place: MV:L14, Chalmers tvärgata 3</span></p>

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Presentation of master thesis

Master thesis presentations at Mathematical Sciences

January 17

13.15-14.15 Boshen Zhang

February 10

10.00-11.00 Hannah Lindmossen