Embedded Voice-Controlled AI Assistant for Robotic Arm Operation in Industrial Automation

Abstract

The integration of Artificial Intelligence (AI) and Natural Language Processing (NLP) into Human–Machine Interfaces (HMI) has become increasingly significant for advancing Industry 4.0. This paper presents the design and implementation of an embedded voice-controlled AI assistant for robotic arm operation in industrial automation. The system employs a Raspberry Pi as the embedded platform, combined with Google’s Gemini large language model (LLM), to interpret voice commands and execute precise movements on a six degrees-of-freedom (6-DoF) robotic arm through Pulse Width Modulation (PWM) control. The assistant architecture integrates speech-to-text conversion, context-aware NLP processing, and servo-based actuation, providing a natural and hands-free interaction between humans and machines. Performance evaluation demonstrates a command recognition accuracy of 90% and an average execution time between 3–10 seconds under laboratory conditions. The results highlight the feasibility of deploying LLM-powered voice assistants on embedded hardware to enhance efficiency and usability in industrial automation. Future work will focus on improving robustness against noisy environments, enabling multilingual support, and extending applicability to real-world industrial settings.