Edge Computing Framework for Enhanced Robotic Adaptivity in Line-Less Mobile Assembly Systems

Procedia CIRP, vol. 127, pp. 26–31

Abstract

In response to the shortage of skilled workers and the increasing diversity of products and variants, integrating adaptive and flexible mobile manipulators into line-less mobile assembly systems (LMAS) stands out as a promising solution. To fully benefit from these robotic systems in LMAS, offloading computationally intensive tasks from mobile manipulators to edge computing systems is essential. This offloading of computational tasks not only lightens the processing load on individual robots but also enhances AI based perception, improving the overall system capabilities in dynamic manufacturing environments. Achieving these goals requires a robotic edge computing framework that serves as the key to flexible and adaptive mobile manipulation in LMAS. To construct such an edge computing framework, a comprehensive set of building blocks is required. These building blocks include a powerful edge system with high processing power, sensor-equipped mobile manipulators with the ability to perceive the environment, and a robust edge-to-robot connectivity. A comprehensive software stack, including software modules for localization and navigation in dynamic assembly environments, AI perception for precise pose estimation of assembly components, and motion planning for interaction between manipulators and assembly components, is crucial. Furthermore, virtualization techniques, a comprehensive deployment strategy, and a detailed description of robot hardware, site, and resources are essential. The proposed edge computing framework presents a solution that addresses mobile manipulators in LMAS and paves the way towards advanced industrial automation. Through implementation in a research assembly environment, the realized proof-of-concept showcased the feasibility of the proposed edge computing framework in a real-world pick-and-place scenario, highlighting its potential to enhance adaptivity and flexibility. There is a potential to refine and expand the framework to accommodate a broader range of industrial applications and streamline diverse manufacturing processes through the integration of mobile manipulators and edge computing within industrial settings.

Authors 7

1. Lukas Bergs corresponding
   Affiliation as printed

   Chair of Production Metrology and Quality Management, Campus Boulevard 30, 52074 Aachen, Germany

2. Guillaume Tréheux
   Affiliation as printed

   Chair of Production Metrology and Quality Management, Campus Boulevard 30, 52074 Aachen, Germany

3. Lukas Schäper
   Affiliation as printed

   Chair of Production Metrology and Quality Management, Campus Boulevard 30, 52074 Aachen, Germany

4. Lucas Manassés Pinheiro de Souza
   Affiliation as printed

   Chair of Production Metrology and Quality Management, Campus Boulevard 30, 52074 Aachen, Germany

5. Sören Münker
   Affiliation as printed

   Chair of Production Metrology and Quality Management, Campus Boulevard 30, 52074 Aachen, Germany

6. Amon Göppert
   Affiliation as printed

   Chair of Production Metrology and Quality Management, Campus Boulevard 30, 52074 Aachen, Germany

7. Robert Heinrich Schmitt Aachen Fraunhofer Institute for Production Technology

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Chair of Production Metrology and Quality Management, Campus Boulevard 30, 52074 Aachen, Germany

   Fraunhofer Institute for Production Technology (IPT), Steinbachstr. 17, Aachen 52074, Germany