Robotic Dogs Gain Traction in Mining Industry for Safety and Efficiency

Quadruped robots, commonly known as “robotic dogs,” are finding increasingly diverse applications in the mining sector as companies look to enhance safety and operational efficiency. Since early trials began around 2020, these four-legged machines have moved from experimental technology to practical tools at several mining operations worldwide.

Equipped with sophisticated sensors including light detection and ranging (LiDAR), thermal cameras, gas detectors, and portable X-ray fluorescence, these robots can perform remote inspections, environmental monitoring, equipment surveillance, and spatial data acquisition with high precision.

“The ability of quadrupeds to navigate complex and hazardous terrains such as underground tunnels, unstable slopes, or tailings facilities makes them ideal for tasks that would be risky or impractical for humans,” explains Nasser Madani, associate professor at Nazarbayev University School of Mining and Geosciences in Kazakhstan.

A key advantage of these robots is their ability to provide continuous and repeatable data collection—an increasingly critical capability for mining operations. According to a recent GlobalData survey, predictive maintenance has become a near-term investment focus for almost half of mines surveyed last year.

Major Mining Companies Embrace the Technology

Several mining giants have already incorporated robotic dogs into their operations. At Glencore’s Kidd Creek mine in Ontario, Canada, Boston Dynamics’ Spot robot assists with inspections in hazardous underground areas, reducing human exposure to dangerous conditions.

In Sweden, LKAB’s Kiruna mine has demonstrated Spot in collaboration with Luleå University of Technology (LTU). The robot helps produce digital twins of mining tunnels using LiDAR scanning and serves as a mobile base for drones, enabling the scanning of areas inaccessible by foot to ensure tunnel safety.

Dwyka Mining Services, operating across Africa, has deployed Spot in what it describes as “some of the dirtiest, darkest and dustiest corners of mining” over the past three years. Jamie van Schoor, CEO of Dwyka, notes that early adopters like Anglo American’s Amandelbult Tumela platinum mine and Rosh Pinah Zinc “have helped catalyse a mindset shift in Africa.”

Dwyka identifies three typical applications for robotic dogs: inspection of “no go areas” such as post-blast or unstable zones; maneuvering in constrained crawl spaces and legacy stopes that defy traditional human and drone access; and routine inspection tasks that benefit from automation.

“As mining operations go deeper and conditions become more extreme, robotic platforms like Spot bridge the widening chasm between data requirements and safe access,” van Schoor explains.

Expanding Applications Beyond Safety Inspections

Another quadruped developer, ANYbotics, has been working with Vale at its Cauê iron ore mine in Brazil. There, its ANYmal robot inspects belts, machine rooms, and milling machinery, collecting thermal images, audio samples, and photographs of equipment.

Julian Mackern, senior go-to-market manager at ANYbotics, highlights how their system addresses particularly dangerous tasks: “ANYmal can safely navigate alongside an active conveyor belt, identifying faulty parts of the belt, pulleys and rollers, to identify any issues before they become costly equipment failures.”

The robots’ roles have evolved significantly since initial proof-of-concept demonstrations that primarily focused on safety inspections. Improvements in sensor integration, autonomy, and ruggedization have expanded their capabilities.

Madani notes that major mining companies are now exploring quadrupeds for “geotechnical monitoring, ore control, and data acquisition in tailings and underground areas,” supported by the robots’ ability for live data offloads, real-time mapping, and route-based data collection.

In research applications, such as legacy tailings projects, robotic dogs have been considered for collecting geochemical data to support resource modeling and improve estimation accuracy, particularly in locations where conventional sampling is limited.

Overcoming Technical Challenges

Deploying robotic dogs in mining environments presents several challenges. These include navigating rough terrain, maintaining stability in wet or loose-ground conditions, limited battery life, and communication issues in underground or remote settings. Dust, humidity, and temperature extremes can also affect sensor performance and hardware durability.

Manufacturers are addressing these issues by enhancing locomotion algorithms for better terrain adaptation, integrating swappable high-capacity batteries, and using ruggedized enclosures to protect electronics. For example, ANYmal is IP67 rated, allowing it to operate in dusty and humid conditions common in mining operations.

While quadrupeds can handle many difficult surfaces, “near-vertical ladders,” “large water bodies,” and “deep mud” still pose challenges, according to Dwyka.

Network constraints represent another hurdle. “While Spot can operate offline on pre-programmed AutoWalks, the real power comes alive with Orbit [Boston Dynamics’ fleet management software], and pervasive Wi-Fi or LTE to enable rerouting, data offload, and mission oversight and alerts,” van Schoor explains.

Mackern notes that data management, rather than robot performance, often presents the biggest challenge for customers. “After ANYmal gathers information from numerous points of interest, visualizing and sharing that data becomes a real challenge,” he says, which led to the development of their Data Navigator asset management platform.

Future Outlook

Over the next three to five years, industry experts expect quadruped robots to evolve from niche applications to widespread adoption in mining operations.

Madani predicts that as sensor payloads become more specialized and integration with digital twins improves, these robots will enable high-frequency, high-resolution data collection in unsafe or inefficient areas for human access.

“Their role will likely expand into routine pre and post-blast assessments, tailings monitoring and real-time mapping of inaccessible zones, supporting more adaptive and predictive mine planning,” Madani explains. “We can also expect tighter integration with AI-driven analytics to automate data interpretation.”

Van Schoor believes the next few years will “mark a tipping point, not just in adoption but in how we design mines for technology, not just with it.” He envisions mining operations with pervasive connectivity and “cobot ecosystems” where drones and quadrupeds work together to create unified digital twins.

“As digital toolboxes evolve, we will see swarms of ground and aerial robots working in tandem, each purpose-built for a different job,” concludes van Schoor. “This isn’t automation replacing humans; it is augmenting them with a flexible, responsive fleet of helpers that makes mining safer, smarter and more sustainable at extreme depths.”