Introduction SLAM (simultaneous localization and mapping)
SLAM (Simultaneous Localization and Mapping) technology has become an essential pillar of modern mining operations, particularly underground, where the absence of a GPS signal and complex geometric conditions mean that autonomous systems must be used to map and locate simultaneously. It enables the creation of detailed 3D maps while locating the mobile platform – be it a robot or a scanner – in real time, without the need for external infrastructure. This technology is particularly valuable in underground mines, where traditional surveying methods are often slow, laborious and risky for operators.
In themining industry, SLAM technology is a key response to the challenges of safety, efficiency and precision. It replaces manual surveys, speeds up the production of recurring maps and reduces the exposure of teams to hazardous areas. By combining high-performance sensors (such as LiDAR) with cutting-edge algorithms, it produces reliable, detailed maps in record time, providing real strategic leverage for mining operations.
What is SLAM technology? Definition and method
This technology meets a major challenge: to move accurately, a system needs to know its position. To determine this position, it needs a reliable map… but this map doesn’t always exist in the first place. SLAM solves this paradox thanks to advanced algorithms capable of simultaneously estimating position and map from data collected by different sensors. In this way, the technology enables you to locate yourself in an environment while constructing, in real time, a map of that environment.
These sensors include :
- LiDAR(Light Detection and Ranging), which generates 3D point clouds from laser pulses.
- Cameras (optical or stereo vision), which analyze textures and visual cues.
- Inertial measurement units(IMUs), which detect movement and orientation.
By merging these data, SLAM produces an accurate digital representation of the environment, while tracking the position of the system generating it. This approach is widely used in fields where GPS is imprecise or non-existent, such as autonomous robotics, augmented reality or underground mapping in mines.
In short, SLAM is a key technology for enabling a machine to “understand” and intelligently orient itself in an unknown space, paving the way for increasingly autonomous and efficient applications.
The evolution of SLAM in recent years
Since its emergence in mobile robotics research in the 1980s, SLAM technology has enjoyed a meteoric rise. Initially limited to university laboratories and experimental robots, it relied on computationally-intensive algorithms and costly sensors, which hampered its widespread adoption.
In the early 2000s, improvements in Extended Kalman Filters (EKF) and the advent of Graph-SLAM approaches led to more accurate maps and reduced error accumulation during surveying. These advances, combined with an increase in the computing power of on-board processors, have paved the way for more practical applications, notably in service robotics and mobile mapping.
The last ten years have marked a turning point:
- The miniaturization and falling cost of LiDAR and IMU sensors have made it possible to develop lightweight, portable SLAM solutions;
- The integration of high-resolution cameras and stereo vision technologies has broadened usage scenarios, particularly in environments where LiDAR alone would be limited;
- Advances in artificial intelligence have improved SLAM’s robustness in complex, repetitive or poorly lit environments.
More recently, the emergence of real-time SLAM on autonomous platforms (drones, service robots, industrial vehicles) has transformed entire sectors such as logistics, construction and mining. In mining, this evolution translates into faster surveys, greater accuracy and enhanced safety, thanks to the ability to map dangerous areas without direct human intervention.
To sum up, in just a few decades SLAM has gone from being an experimental concept reserved for researchers to a mature, accessible and indispensable technology in many industrial sectors, with adoption growing steadily in step with hardware and software innovations.
What are the advantages of SLAM over traditional surveying methods?
Traditional surveying methods, such as manual topography or the use of fixed total stations, are often time-consuming, mobilize field staff and sometimes require operations to be interrupted to carry out measurements. In a demanding environment such as mining, these constraints can quickly become costly and risky.
SLAM(Simultaneous Localization and Mapping) technology provides a modern, efficient response to these limitations:
- Fast data acquisition
SLAM systems, whether handheld, vehicle-mounted or integrated into a drone, can capture millions of points per second and cover vast areas in just a few minutes. This enables frequent surveys to be carried out without disrupting mining activity. - Enhanced safety
By avoiding exposing operators to unstable or hard-to-reach areas, SLAM considerably reduces risks to personnel. Inspections can be carried out remotely, via autonomous or remotely-operated platforms. - Accuracy tailored to industrial needs
Thanks to the fusion of sensors (LiDAR, cameras, IMU), SLAM produces detailed 3D maps, often with sufficient accuracy for planning, geotechnical monitoring or volume calculations. - Flexibility and adaptability
Unlike static surveys, SLAM can be rapidly deployed in a variety of contexts: mapping narrow galleries, measuring stockpiles, inspecting shafts, or surveying complex underground infrastructures.
In short, SLAM combines speed, safety, precision and flexibility, making it a particularly attractive alternative to traditional methods, especially in complex environments.
Mining applications
SLAM technology is playing an increasingly strategic role in the mining sector, particularly in underground environments where GPS is unusable. This paves the way for faster, safer and more efficient operations.
Rapid mapping of tunnels and galleries
With SLAM systems, teams can carry out complete 3D surveys of galleries, shafts and intersections without interrupting operations. A mobile scanner or LiDAR-equipped drone can cover vast sections in a matter of minutes, producing accurate models that can be used for planning, maintenance and safety purposes.
Safe inspection of hazardous areas
SLAM enables a robot or drone to be sent into unstable areas, such as weakened galleries or hard-to-reach shafts, for inspection without exposing personnel. Readings are instantly available for use by engineers.
Precise calculation of inventory volumes
By generating a high-precision 3D point cloud, SLAM makes it easy to calculate the volume of mining stockpiles (ore, coal, aggregates) or waste materials. These rapid measurements optimize inventory management and reduce the need for time-consuming manual methods.
Geotechnical monitoring and change detection
SLAM readings taken at regular intervals detect deformations or movements in the walls, helping to anticipate the risk of collapse. This continuous monitoring enhances the overall safety of the site.
Autonomous navigation for mining robotics
Integrated into autonomous vehicles or robots, SLAM technology enables them to move around in complex environments, avoid obstacles and update their maps in real time, improving the automation of underground operations.
Which SLAM system should you choose for your mining surveys?
GreenValley International products
GreenValley International is a recognized player in the field of 3D mapping and LiDAR technologies, offering complete solutions for the collection, processing and analysis of geospatial data. The company develops a wide range of equipment, from portable scanners to mobile systems mounted on vehicles or drones, to meet the needs of the most demanding sectors, including the mining industry.
Their expertise is based on the integration of high-precision sensors and advanced algorithms, notably SLAM technology, to provide fast, reliable and exploitable surveys.
LiAir H600 – Portable LiDAR SLAM scanner
The LiAir H600 represents a major advance in the LiDAR SLAM sensor range, designed to offer unrivalled data collection capacity in complex environments such as mining sites. Its main asset is its unlimited return technology, which delivers extremely high point density. Under normal conditions, the sensor records up to 7 returns per pulse (compared with 5 for previous generations), but it can theoretically provide an almost infinite number of returns when required.
This performance translates into better penetration of vegetation cover and structures, enabling precise capture of ground topography, even in the presence of dense canopy or masking elements. For open-pit mining operations, this means fewer operational constraints: no need for slow flights or tight grids, the H600 guarantees complete coverage in the shortest possible time.
With a range of up to 750 metres (ideally used at 200 m or less for optimum accuracy), the LiAir H600 is a versatile tool:
- Open-pit and surface mining: fast, accurate mapping of working faces, pits and extraction zones.
- Forestry and environment: ability to collect detailed data even in overcast conditions.
- Topography and construction: high-precision surveys for development and infrastructure projects.
The LiAir H600 combines range, point density and flexibility, making it a strategic choice for players in the mining sector looking to optimize the accuracy and speed of their surveys.
LiGrip O2 Lite – Compact mobile SLAM solution
The LiGrip O2 Lite has been designed as a portable SLAM solution combining lightness, compactness and performance. More affordable than high-end models, it nevertheless makes no compromise on the quality of the data it collects. Thanks to its ergonomic format and low weight, it is the ideal tool for professionals who need to intervene quickly in difficult-to-access or restricted environments, such as underground galleries, narrow tunnels or areas congested by infrastructure.
Its optimized SLAM technology ensures stable accuracy, even in complex conditions where light and spatial configuration vary greatly. This makes it particularly suitable for rapid mapping missions and operational inspections, without the need for heavy logistics.
With the LiGrip O2 Lite, operators have a flexible solution for :
- Volume surveys: rapid assessment of the volume of materials extracted or stored.
- Surface-underground transition zones: continuity of surveys between different areas of a mining operation.
- Confined spaces: reliable data collection in hard-to-reach environments where larger solutions would be impractical.
- Rapid inspections: express deployment to get a clear view of an area without interrupting operations.
The LiGrip O2 Lite combines mobility, simplicity and efficiency, making it a must-have SLAM sensor for mining companies looking for a practical, cost-effective solution to complete or accelerate their survey campaigns.
LiMobile M2 Ultra – High-capacity mobile LiDAR system
The LiMobile M2 Ultra is a high-performance mobile SLAM system designed to equip land vehicles and provide continuous, fast and accurate mapping over large areas. By integrating a latest-generation LiDAR sensor with an advanced SLAM module, it enables massive data collection while considerably reducing field deployment time.
Designed for mining and industrial environments, the LiMobile M2 Ultra offers high point density and wide coverage, guaranteeing faithful representation of the terrain, even in complex contexts. Its ability to be installed on mobile platforms (all-terrain vehicles, trucks or other suitable equipment) makes it an essential tool for linear surveys and large-scale areas.
Its main assets include:
- Large-scale data collection: ideal for access roads, extensive working faces or surface mine workings.
- Operational efficiency: the ability to cover kilometers of terrain quickly, without interrupting on-site activities.
- Accuracy and stability: the on-board SLAM system ensures reliable localization even in environments where GNSS is limited or disrupted.
- Versatility of use: deployable not only in mining operations, but also for surveying applications, infrastructure construction, or linear corridor inspections (roads, railroads, pipelines).
With its range and power, the LiMobile M2 Ultra is the benchmark solution for companies looking to optimize the productivity of their surveys, combining rapid deployment and reliable data collection.
Mapping and mining inspection: which drones to choose?
The choice of a drone for the mining sector depends on several factors: expected precision, flight autonomy, robustness, compatibility with specialized sensors such as the LiGrip H300, and ability to operate in complex environments. The DJI Matrice range stands out for its reliability, modularity and adaptability to the demanding conditions encountered in mining operations.
Matrix 4 Series
The Matrix 4 Series is a versatile, high-performance solution, ideal for mapping, inspection and surveillance in mining environments. Equipped with advanced sensors (wide-angle, zoom and thermal cameras depending on version) and intelligent navigation systems, it offers enhanced precision even in low-visibility environments.
Its robustness, extended autonomy and advanced mission-planning functions make it an effective tool for rapid aerial surveys and inspections of hard-to-reach areas.
Matrix 350 RTK – Compatible with LiAir H600
The Matrice 350 RTK is a robust industrial drone (IP55 protection rating) designed to withstand the dust, humidity and climatic variations often encountered on mining sites.
It offers :
- Autonomy of up to 55 minutes.
- An integrated RTK system for centimetric precision.
- Compatibility with a wide range of payloads, including the LiAir H600.
This compatibility makes it possible to combine the stability and range of the Matrice 350 RTK with the power of the LiAir H600 for accurate aerial SLAM surveys, even in limited or absent GPS environments.
Matrix 400 – Compatible with LiAir H600
The Matrice 400 RTK, the latest model in the range, takes performance even further. It offers up to 59 minutes of flight time, increased payload capacity and the ability to carry several sensors simultaneously.
Thanks to its advanced RTK system and resistance to hostile environments, it is perfectly suited to large-scale mining operations requiring fast, detailed surveys.
Like the Matrice 350 RTK, the Matrice 400 is compatible with the LiAir H600, making full use of the capabilities of this LiDAR SLAM scanner for 3D mapping and volume calculation in mining environments.
Challenges and prospects for SLAM
While SLAM technology has already transformed the way surveys and inspections are carried out in mining environments, its development still faces a number of technical and operational challenges.
Challenges to meet
First and foremost, the extreme environmental conditions of underground mines place severe demands on sensors: dense dust, humidity, flooded areas, high temperatures or highly reflective surfaces can alter measurement accuracy. Geometric degeneration, caused by the repetition of shapes or textures in tunnels, also represents an obstacle: SLAM algorithms can lose their bearings when there are no distinctive elements to correct the trajectory.
Another challenge is managing the massive volume of data generated by 3D surveys. Storing, processing and sharing this data requires high-performance IT infrastructures and software capable of rapidly processing complex point clouds. Added to this is the issue of hardware and software costs, which can hamper large-scale adoption, especially for smaller mining sites.
Promising prospects
Despite these challenges, the prospects for SLAM in the mining sector are considerable. Current research is focusing on more robust algorithms, capable of maintaining high accuracy even in degraded environments, and on the increased integration of artificial intelligence to optimize recognition of key features in point clouds.
The future will also see the development of cooperative multi-robot SLAM, where several platforms (ground robots, aerial drones, autonomous vehicles) will work together to map vast underground networks in record time. This approach will make it possible to pool data, improve coverage and reduce response times.
Finally, the integration of SLAM with intelligent mining systems, combining automation, IoT* sensors and real-time analysis, will pave the way for safer, more efficient and fully digital mines.
*IoT (Internet of Things) sensors are connected devices capable of collecting physical or environmental data, then transmitting it via the Internet or a local network for analysis and processing.
Conclusion
SLAM technology, and in particular mobile LiDAR-SLAM, is profoundly transforming underground mining practices. It combines safety, speed and precision to meet the extreme constraints of GPS-free environments. Despite technical challenges (environmental conditions, complex geometry, massive data), progress is constant, thanks in particular to multi-sensor fusion and the emergence of multi-robot systems.
With a vision of the future, SLAM’s cooperative, autonomous and robust systems promise to revolutionize mine mapping, inspection and geotechnical management. They contribute to safer, more efficient and better-informed operations, driving the digital transition of the mining sector.
Frequently asked questions – FAQ
What are the best SLAM algorithms for mapping complex mine environments?
Mining environments present many challenges: low light levels, lack of GNSS signal, dust and irregular structures. The most effective SLAM algorithms in this context generally combine vision (Visual SLAM) and LiDAR (LiDAR SLAM) to maximize accuracy. Among the most widely used are Google’s LOAM (Lidar Odometry and Mapping), Cartographer and Hector SLAM, renowned for their robustness in the face of changing textures and cramped environments.
Can robotic SLAM be used in all mines?
In theory, yes. Robotic SLAM is equally well-suited to underground mines and open-pit operations, provided the system is configured and calibrated according to site constraints. However, certain environments that are extremely unstable, wet or subject to mechanical interference may require enhanced or hybrid solutions, combining several types of sensors (LiDAR, IMU, cameras, etc.).
Where can you find comprehensive technical documentation for understanding and implementing SLAM in an industrial context?
Equipment manufacturers such as GreenValley International often offer detailed technical guides and user manuals. There are also academic resources (scientific articles, IEEE publications) and open source tutorials on platforms such as GitHub or ROS Wiki, ideal for delving deeper into the configuration and optimization of an industrial SLAM system.
How is the SLAM market evolving and what are the prospects?
The SLAM market is growing rapidly, driven by the rise of automation, robotics and 3D surveying in sectors such as mining, construction and logistics. Current trends include: the increased integration of artificial intelligence to improve recognition of environments, the optimization of multi-sensor data fusion and the development of more compact SLAM systems, compatible with autonomous drones and robots. Forecasts predict even wider adoption over the next few years, with ever more accurate and accessible solutions.