How do autonomous vehicles and robots work in mining operations?

Autonomous vehicles and robots in mining operations use advanced technologies including GPS, radar, and LiDAR to automate the transportation of materials and other tasks within mining sites.

These systems allow driverless trucks to transport mining materials around a site using GPS, wireless/LTE communication and perceptive technologies.

An autonomous haulage system is a fleet management system designed for mines that relies on a wireless connection to create an interconnected system equipping mining machines with GPS, vehicle controllers, and obstacle detection systems.

Key Points

• Autonomous mining vehicles use multiple sensors including GPS, LiDAR, radar, and cameras to navigate and detect obstacles
• Fleet management systems coordinate autonomous equipment from centralized control centers, often located far from the mine site

Autonomous haulage systems enable vehicles to operate 24/7 and deliver business results for stakeholders

Automated drilling systems, sometimes referred to as drilling robots, are commonly used in mines for blast hole drilling, exploration, and production drilling

Autonomous mining technology allows workers to operate equipment from afar instead of in hazardous environments

Understanding Autonomous Mining Technology

Autonomous technology has been used at mines for over 30 years, with Komatsu deploying Field Management Software for managing operations at mines in Japan in 1990, and achieving commercial deployment in Chile in 2007 and in Australia in 2008.

One of the most significant early uses of autonomous mining vehicles was by the Rio Tinto Group at Australia's Mine of the Future in 2008, where workers operate an autonomous mining fleet from a control center in Perth, and just six years into the operation, autonomous trucks had hauled 200 million metric tons.

The technology has evolved significantly since those early deployments. Modern autonomous trucks utilize advanced technologies, such as artificial intelligence, machine learning, and sensors, to navigate and perform their tasks autonomously.

Smart mine technology integrates artificial intelligence (AI), internet of things (IoT), automation, and data analytics into existing mining operations, helping organizations streamline their operations with a focus on enhancing safety and productivity.

Autonomous mining systems can be implemented through different approaches. There are two approaches to introducing autonomous technology in the mine environment: an all-or-nothing grand vision approach, where the mine goes from manned-vehicles to a fully-automated unmanned fleet in one step, or a moderated user-assisted approach.

Miners can opt for an incremental approach where they can begin with a user-assisted approach before transitioning to full autonomy overtime.

How It Works

1. Sensor Systems and Perception

Autonomous trucks are equipped with a range of sensors, including GPS, LiDAR, radar, and cameras.

Multi-sensor fusion perception systems integrate LiDAR, millimeter wave radar and camera to achieve complementarity of multi-sensor functions, ensuring redundancy for safe autonomous driving and enabling stable omnidirectional perception of the surrounding environment, covering 360° range.

3D SLAM technology combined with GPS and inertial navigation creates high-precision point cloud maps to achieve accurate positioning and autonomous navigation, while neural network algorithms are used to accurately identify target attributes through deep learning and output surrounding environmental information in real time.

It's possible for autonomous vehicles and equipment to avoid colliding with objects or people in their path.

2. Vehicle Conversion and Control

The first step in automating a vehicle is converting it to drive-by-wire by adding actuators and hydraulic controls. This conversion allows the vehicle's steering, braking, and acceleration to be controlled electronically rather than mechanically, enabling computer systems to take over driving functions.

Every vehicle streams data on wheel wear, hydraulic pressures, motor temperatures, and battery health to central analytics hubs through continuous telemetry.

Anomalies in vibration, temperature, or pressure are caught early, triggering service alerts well before a mechanical fault can create a safety hazard, breakdown, or collision.

3. Fleet Management and Coordination

The centralized computer system is controlled by an artificial intelligence (AI) algorithm, called Q-Learning, that can optimize fleet dispatching in real time, managing the truck dispatch by altering vehicles' paths, changing loading and drop-off points, and managing maintenance needs.

The system can dynamically update the dispatching plan based on maintenance needs, payload material grade, vehicle queues, and traffic patterns.

Multiple haulers can work together as a connected fleet with fleet management systems, often referred to as Autonomous Haulage Systems (AHS), using a combination of sensors and GPS technology to navigate the mining site and transport material safely and efficiently.

The AHS-enabled haul trucks can be controlled from a remotely operated control center.

4. Specialized Robotic Systems

Beyond haul trucks, mining operations deploy various specialized autonomous systems. Rio Tinto's Automated Drill System (ADS) allows a remote operator, far away from the dangerous mine face, to operate four autonomous rigs fully simultaneously through a single console.

Automated drilling systems operate continuously, drilling holes with consistent accuracy and speed, and therefore increase the overall output of mining operations.

Drilling robots commonly take the form of rovers and full-scale blasting rigs, and autonomous drilling and blasting platforms are equipped with a suite of sensors.

GPS and vision systems aid in navigation and path planning, while sophisticated measurement tools enable these systems to report back on metrics like blast fragmentation, with this data reported back to a control system that enables operators to optimize historical blast data across the entire fleet.

Why It Matters

Autonomous mining technology addresses critical industry challenges around safety, productivity, and operational efficiency. Many activities within mines are hazardous, such as surveying, extraction, haulage, and dozing, and increasingly, these activities are being conducted by autonomous robotic systems, saving money and improving productivity.

Automating drilling and blasting activities takes workers away from the mine face, which is one of the most hazardous areas within a deep underground mine.

The operational benefits extend beyond safety improvements. There's no need for shift changes or lunch breaks, and the machines always operate within the parameters set within the automatic haulage system, eliminating the production slowdowns that can happen with human workers and enabling more reliable and efficient production planning.

Compared to human drivers, autonomous trucks can operate 24/7, reduce the risk of accidents, and optimize routes to minimize fuel consumption and increase productivity.

Related Terms

• Autonomous Haulage System (AHS): A comprehensive fleet management system that coordinates driverless trucks and other mining vehicles through wireless communication, GPS, and obstacle detection technologies.

• LiDAR (Light Detection and Ranging): A sensor technology that uses laser pulses to create detailed 3D maps of the surrounding environment, essential for autonomous vehicle navigation and obstacle detection in mining operations.

• Fleet Management System (FMS): Centralized software that monitors, coordinates, and optimizes the operation of multiple autonomous vehicles and equipment across a mining site, managing tasks, routes, and maintenance schedules.

Frequently Asked Questions

What types of mining equipment can be automated?

From mining to loading to hauling, the industry can leverage end-to-end solutions for fully autonomous mining operations.

Unmanned vehicles may include any one or more of earth moving vehicles (such as front end loaders), and drill rigs for drilling blast holes.

Vehicle and equipment manufacturers have risen to meet demands with drills, dozers, underground loaders, and other vehicles.

How do autonomous vehicles navigate underground mines without GPS?

Path planning in underground environments presents unique challenges due to the lack of GPS signals, and GPS and GNSS signals cannot penetrate underground environments, eliminating the absolute positioning reference that surface autonomous systems rely on for drift correction.

Autonomous navigation in mining tunnels is challenging due to the lack of satellite positioning signals and visible natural landmarks, leading to autonomous navigation approaches based on artificial passive landmarks, whose geometry has been optimized to ensure drift-free localization of mobile units typically equipped with lidar scanners.

Can autonomous and human-operated equipment work together?

Yes, modern mining operations often use mixed fleets. When the truck driver gets close to the shovel and they are able to communicate with each other, the autonomous system takes over and performs the spotting, and similarly, when the driver enters a long-haul corridor, the auto-pilot takes over and maintains optimal speed.

Methods include providing identifiable access roads for manned and unmanned resources within the mine area, and changing the manned and unmanned zones as mining operations progress in the mine area having regard to the requirements of the mining operations.

Last updated: July 20, 2026. For the latest energy news and analysis, visit stakeandpaper.com.