Enabling Digitalization in Modular Robotic Systems Integration

TL;DR

This PhD investigates how digitalization can accelerate modular robotic systems integration by targeting three pivotal areas: acquisition, integration, and deployment. It develops a constraint based configurator (RoboCIM) to resolve device compatibility, analyzes URDF to identify interoperability gaps, and surveys digital twins for unit-level manufacturing to enable predictive maintenance and optimization. The work offers a formal configurator framework, a detailed critique and enhancement plan for URDF, and a modular digital twin architecture with a proof of concept, collectively advancing faster deployment, reduced vendor lock-in, and enhanced reuse of robotic devices. While promising, industrial validation and broader scalability remain to be demonstrated. Overall, the study provides concrete methodologies, data sets, and architectural blueprints that stakeholders can adopt to drive efficiency and cost reductions in robotic systems integration.

Abstract

Integrating robot systems into manufacturing lines is a time-consuming process. In the era of digitalization, the research and development of new technologies is crucial for improving integration processes. Numerous challenges, including the lack of standardization, as well as intricate stakeholder relationships, complicate the process of robotic systems integration. This process typically consists of acquisition, integration, and deployment of the robot systems. This thesis focuses on three areas that help automate and simplify robotic systems integration. In the first area, related to acquisition, a constraint-based configurator is demonstrated that resolves compatibility challenges between robot devices, and automates the configuration process. This reduces the risk of integrating incompatible devices and decreases the need for experts during the configuration phase. In the second area, related to integration, the interoperable modeling format, Unified Robot Description Format (URDF), is investigated, where a detailed analysis is performed, revealing significant inconsistencies and critical improvements. This format is widely used for kinematic modeling and 3D visualization of robots, and its models can be reused across simulation tools. Improving this format benefits a wide range of users, including robotics engineers, researchers, and students. In the third area, related to deployment, Digital Twins (DTs) for robot systems are explored, as these improve efficiency and reduce downtime. A comprehensive literature review of DTs is conducted, and a case study of modular robot systems is developed. This research can accelerate the adoption of DTs in the robotics industry. These insights and approaches improve the process of robotic systems integration, offering valuable contributions that future research can build upon, ultimately driving efficiency, and reducing costs.

Figures (30)

• Figure 1: Illustration of the initial goal of the project, showing an e-commerce platform for purchasing modular robot systems, followed by the deployment and maintenance during operation of the purchased system.
• Figure 2: The project scope is limited to single robot systems, as shown with the red oval.
• Figure 3: The connections assumed between the output of the RQs (illustrated by the solid arrows) and how this can be used in the addressing of other RQs. The RQs are mapped to the part of modular robotic systems integration that they address.
• Figure 4: Overview of the technical process of modular robotic systems integration, entailing acquisition (phase 1 and 2), integration (phase 2 and 3), and deployment (phase 3 and 4). The chapters in this thesis are presented with their associated Research Questions and contributions. The blend of colors in the chapters shows the colors of the parts of the process that the chapters cover. The arrows between phase 1 and 2 indicate an iterative process between these phases.
• Figure 5: Overview of the chapters, Research Questions, contributions, and the publications related to each.