In May 2026, the National Mine Safety Supervision Bureau and the Ministry of Industry and Information Technology jointly launched the “Mining Robot Application Verification Pilot”, focusing on seven high-risk scenarios such as excavation, mining, and transportation. It is mandatory for equipment to pass the mining product safety mark certification and conduct 6-9 months of real-life working condition verification. This marks the shift from “demonstration display” to “actual assessment” in the application of mining robots.
According to news on June 1, 51WORLD released the world’s first physically intuitive world model 51World in the first half of the year
Model, and released 51Claw, an Agent base system specially built for embodied intelligence, integrating 51World Model with OpenClaw to help AI enter the physical world.
Smart mines are a trillion-level market with broad prospects. There are thousands of coal mines and tens of thousands of non-coal mines in our country. Unmanned underground operations have become an irreversible rigid trend.
However, it is not difficult to “put advanced equipment into the mine”. What is difficult is to make it ready for use and stable.
The mine environment is complex, with characteristics such as limited vision, hidden disasters, and continuous dynamic evolution of space. For the “brain” of the robot, this is a strange and high-risk unstructured space.
Robots cannot “run and test” like in the laboratory. One misjudgment may lead to irreparable safety accidents.
The deeper problem is that robots generally lack global spatial cognition and system-level linkage capabilities. No matter how agile their movements are, they are just “moving islands of information.”
The essence of the current industry bottleneck lies not in the insufficient number of robots deployed, but in the lack of a system that can support environmental understanding, decision-making, and verification.
This physical AI system can, on the one hand, improve the robot’s cognition and decision-making level in complex environments. On the other hand, it can eliminate high testing costs and unacceptable safety risks in simulation and synthetic data in advance, transforming underground verification from “unaffordable” to “controllable, reproducible, and iterable.”
Unmanned mining can be roughly divided into two branches. Open-pit mines have initially achieved large-scale application, represented by unmanned mining trucks; while the excavation, inspection, rescue and other aspects of underground mines are still technically difficult, and are also the “last mile” that is the most urgent and safety priority in the industry.
Currently, various types of mining robots come in various forms, such as unmanned mining trucks, inspection robot dogs, excavation robots, emergency rescue platforms, etc., but what they all lack in common is a unified physical AI base.
Underground, the unified physical AI base can solve four long-standing “distortion” problems in a targeted manner: spatial semantic alignment based on multi-source data fusion to eliminate structural deviations that “drawings do not match the site”; through cross-comparison of screen recognition and positioning ledgers, correction of human
Distortion of employee ledgers; relying on close-in collection of inspection equipment to directly connect the data to the center and binding it to 3D assets, replacing error-prone manual meter reading; building an automated processing closed loop to promote the upgrade of alarms from a single pop-up window to a full-process management of “work order generation – linked processing – result review – case closure and leaving traces”.
At the beginning of 2026, there will be intensive demand for simulation in the fields of autonomous driving of mining trucks and construction machinery.
51WORLD’s simulation capabilities have supported mining truck autonomous driving customers to carry out high-fidelity sensor simulation, dust environment simulation, complex vehicle dynamics modeling, 3D Gaussian scene reconstruction and automated testing. This is not only a demonstration of the feasibility of the physical AI base in open-pit mine scenarios, but also provides a reusable methodological reference for technical breakthroughs in underground mines.
In terms of smart ports, 51World Model connects terminal TOS and equipment data to achieve full-time monitoring, process optimization, predictive simulation and emergency security; it also provides closed-loop simulation of port intelligent equipment for unmanned engineering machinery, supporting perception-planning-control and HIL verification.
Multi-equipment collaboration, real-time data-driven twinning, and highly isomorphic with underground transportation system scheduling.
Industry insiders believe that as artificial intelligence moves from large language models to world models, physical AI is becoming a key underlying variable in building a future smart economy.
Under this trend, the industry will continue to deepen the “chip – system – ecology – application” full-stack layout to open up a two-way channel between humans and AI: allowing humans to enter the digital world more immersed, and allowing AI to act more safely in the physical world.
