Autonomous Underground Loading and Transport Systems – Robust Safety architecture and Practical Implementation
Author: Dr. Eric Pohlmann, Managing Director, Nerospec SK GmbH, Velbert/Germany
DOI: 10.66356/mrg.2026.05.02.ENAULTS
Automation in the mining industry has experienced a significant surge in development thanks to advances in the three areas of sensor technology, artificial intelligence (AI) and software architecture. Autonomous underground loading and transport systems boost productivity, improve safety and enable more efficient use of resources. Robust, cost-effective LIDAR and RADAR sensors from the automotive industry, together with modular software frameworks, form the basis for practical, bespoke automation solutions in mining. The Autonomous Operator System (AOS) developed by Nerospec SK GmbH, Velbert/Germany, enables fully autonomous driving cycles without human supervision. Control is carried out without cameras or broadband networks, enabling the system to operate reliably even in isolated underground environments. An integrated safety architecture, certified to ISO 13849 and IEC 61508, continuously monitors the vehicle’s functions and actively intervenes when necessary to bring the vehicle into a safe state. This intelligent interaction between safety-critical control and AI logic creates a dynamic balance between productivity and safety. The results show that autonomous systems developed in accordance with safety-critical principles represent a realistic and scalable solution for the mining industry. The concept presented makes a key contribution to the safe introduction of autonomy into industrial practice. The article is based on the authors presentation at the “MiningForum 2026”, held in Berlin/Germany from 18th to 19th June 2026.
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