INTELLIGENT AND SAFETY-CERTIFIED ROBOTIC SYSTEMS: INTEGRATING DEEP LEARNING VISION WITH DETERMINISTIC EMBEDDED CONTROL FOR INDUSTRY 4.0

Abstract

Today industrial automation requires the robotics system to be intelligent, deterministic, adaptive with integration of AI-driven perception, fault-tolerant, and certifiably safe for human collaboration. These critical needs of modern industrial automation cannot be fulfilled by use of already existing traditional frameworks (PLC-based control, rule-based vision, Robot Operating system 1-ROS1, AI only vision robotics, and Collaborative Robots -COBOTS etc.). This paper establishes a holistic design to allow a unification of perceived, determinant control, communication and safe subsystems to deliver safely executed robotic tasks on a real time basis in smart factories. The proposed framework unites both deep learning-based computer vision object detection and defect localization as well as embedded microcontroller devices with deterministic control algorithms, connecting them all together via middleware (ROS2/DDS) and time-synchronized via EtherCAT fieldbus systems. The system was experimentally tested in a simulated pick-inspect-place workcell with end-to-end latency of under 40 ms and object detection accuracy of over 94%, and robust reaction to failures on communication, perception, and actuation layers. Safe human-robot collaboration was achieved through passing the safety compliance tests that met the ISO 10218 and IEC 61508 requirements of safe response times. Results show the scalability of the architecture to multi-node robotics, and appreciation of the trade-offs between adaptive intelligence and deterministic control and appreciation of the challenges of explainability, fault tolerance, and interoperability in Industry 4.0 ecosystems are noted. The overall research illustrates the feasibility of the combination of computer vision and embedded electronics in an autonomous robot system that would be both intelligent and certifiably safe.

Keywords

Robotics;Industrial Automation;Computer Vision;EmbeddedE electronics; Real-Time Control; EtherCAT; ROS 2; DDS; Fault Tolerance; Safety Standards; Industry 4.0; Cyber-Physical Systems; Human–Robot Collaboration; Predictive Maintenance; Smart Manufacturing