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infrastructure costs, but to who could build things. Developers who had no interest in managing physical servers could suddenly deploy sophisticated systems because the complexity had been abstracted away. The underlying technology didn’ t simplify. The access did. That shift produced more capable engineers, not fewer, because more people could participate. Robotics is at the same point. The frameworks exist. What’ s been missing is the abstraction layer that lets the people who understand the problem get their hands on it.
Platforms built on top of ROS2 now offer browser-based environments, simulation, and SDKs in languages that mainstream developers already know. A developer can model a production scenario, test behaviors in simulation and de-risk an application before any hardware is ordered.
The economics of experimentation
The traditional path to automation frontloads the risk. You engage specialists, commit to hardware, run the integration and then discover, over months, whether the outcome meets expectations. The Manufacturing Technology Centre has documented this research-to-deployment gap in detail. It is a significant driver of stalled automation projects, and it falls hardest on the businesses that cannot absorb the cost of a project that doesn’ t deliver.
When you prototype in simulation before hardware is involved, the equation changes. Experiments become cheap. Iteration compresses. The decision to buy equipment is made on the basis of something already tested, not a specialist’ s estimate.
Getting a robot operational is not primarily a hardware problem
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