Records in automated excavation.

in StemSocial9 hours ago

Records in automated excavation.



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Records in automated excavation.


While the world watches humanoid theft, autonomous cars and smart drones, a silent revolution is happening in mining, which is also used for the raw materials of those technologies, the company Bedrock Robotics has just announced an impressive record, its autonomous excavators moved around 50,000 cubic meters of earth in a single project, preparing the ground for a gigantic 52 hectare industrial facility.


All of this working alongside human-operated trucks in the same traditional workflow as civil construction and this integration may seem simple, but it is exactly the opposite, it is one of the biggest challenges of automation in real life. For companies there is a growing problem, there is no shortage of heavy machines, there is a lack of experienced operators and when someone is found, the monotony of repetitive tasks kills any motivation.


Operators become bored and fatigued doing the same repetitive activity for months, loading trucks in remote locations in sweltering heat and dust; That is why Bedrock Robotics is attacking precisely that bottleneck, leaving the repetitive part for AI. At the heart of all this is the Bedrock Operator, an AI controller capable of operating excavators from 20 to 80 tons.




They were not programmed manually.


There are no engineers telling you exactly how to move the arm or measure force, the founders, almost all veterans of Bedrock Robotics, followed another philosophy, letting the machine learn directly with real data from human operators. Bedrock Robotics went from simulation to the first functional machine nicknamed Fred in just 4 months.


Shortly after, it was already testing autonomy in the open field, each new day of operation generates data and each data improves the model, it is a continuous evolution similar to what we see in language models, only instead of generating sentences, the algorithm generates trajectories, angles, depths, high-precision motor decisions.


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