Implementation of AutomationML for Flexible Programming for Switching Robot Hardware

Tsn, Wishley (2026) Implementation of AutomationML for Flexible Programming for Switching Robot Hardware. Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.

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Abstract

The rapid evolution of robotics in modern industries has underscored a critical limitation: the inflexibility of hardware-software integration in traditional robotic systems, which demands extensive reprogramming whenever hardware components are swapped or upgraded. This research proposes a novel solution by leveraging AutomationML (AML), a standardised XML-based data exchange format (IEC 62714), to develop a flexible programming framework that enables seamless hardware reconfiguration in robotic systems. The framework introduces an intuitive drag-and-drop interface, minimizing manual coding and making hardware switching accessible to users with diverse technical backgrounds. Key objectives include: (1) designing an AML-based framework and workflow for efficient hardware configuration, (2) evaluating its performance through testing focused on integration speed, adaptability, and usability, and (3) enhancing the framework with a CSV-based logging system for traceability and performance analysis. The methodology involves developing the software framework using Python and Arduino IDE, targeting common robotic components such as actuators and sensors, over a 7-month timeline from February to September 2025. The expected outcome is a reproducible, plug-and-play workflow that reduces the time and cost of hardware changes, enhancing system flexibility and scalability. By pioneering AML’s application in this context, this research contributes to Sustainable Development Goals 8 (Decent Work and Economic Growth) and 9 (Industry, Innovation, and Infrastructure), fostering economic efficiency and innovation in industrial automation.